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  • Intelligence per watt

    My thinking on the concept of intelligence per watt started as bullets in my notebook. It was more of a timeline than anything else at first and provided a framework of sorts from which I could explore the concept of efficiency in terms of intelligence per watt. 

    TL;DR (too long, didn’t read)

    Our path to the current state of ‘artificial intelligence’ (AI) has been shaped by the interplay and developments of telecommunications, wireless communications, materials science, manufacturing processes, mathematics, information theory and software engineering. 

    Progress in one area spurred advances in others, creating a feedback loop that propelled innovation.  

    Over time, new use cases have become more personal and portable – necessitating a focus on intelligence per watt as a key parameter. Energy consumption directly affects industrial design and end-user benefits. Small low-power integrated circuits (ICs) facilitated fuzzy logic in portable consumer electronics like cameras and portable CD players. Low power ICs and power management techniques also helped feature phones evolve into smartphones.  

    A second-order effect of optimising for intelligence per watt is reducing power consumption across multiple applications. This spurs yet more new use cases in a virtuous innovation circle. This continues until the laws of physics impose limits. 

    Energy storage density and consumption are fundamental constraints, driving the need for a focus on intelligence per watt.  

    As intelligence per watt improves, there will be a point at which the question isn’t just what AI can do, but what should be done with AI? And where should it be processed? Trust becomes less about emotional reassurance and more about operational discipline. Just because it can handle a task doesn’t mean it should – particularly in cases where data sensitivity, latency, or transparency to humans is non-negotiable. A highly capable, off-device AI might be a fine at drafting everyday emails, but a questionable choice for handling your online banking. 

    Good ‘operational security’ outweighs trust. The design of AI systems must therefore account not just for energy efficiency, but user utility and deployment context. The cost of misplaced trust is asymmetric and potentially irreversible.

    Ironically the force multiplier in intelligence per watt is people and their use of ‘artificial intelligence’ as a tool or ‘co-pilot’. It promises to be an extension of the earlier memetic concept of a ‘bicycle for the mind’ that helped inspire early developments in the personal computer industry. The upside of an intelligence per watt focus is more personal, trusted services designed for everyday use. 

    Integration

    In 1926 or 27, Loewe (now better known for their high-end televisions) created the 3NF[i].

    While not a computer, but instead to integrate several radio parts in one glass envelope vacuum valve. This had three triodes (early electronic amplifiers), two capacitors and four resistors. Inside the valve the extra resistor and capacitor components went inside their own glass tubes. Normally each triode would be inside its own vacuum valve. At the time, German radio tax laws were based on the number of valve sockets in a device, making this integration financially advantageous. 

    Post-war scientific boom

    Between 1949 and 1957 engineers and scientists from the UK, Germany, Japan and the US proposed what we’d think of as the integrated circuit (IC). These ideas were made possible when breakthroughs in manufacturing happened. Shockley Semiconductor built on work by Bell Labs and Sprague Electric Company to connect different types of components on the one piece of silicon to create the IC. 

    Credit is often given to Jack Kilby of Texas Instruments as the inventor of the integrated circuit. But that depends how you define IC, with what is now called a monolithic IC being considered a ‘true’ one. Kilby’s version wasn’t a true monolithic IC. As with most inventions it is usually the child of several interconnected ideas that coalesce over a given part in time. In the case of ICs, it was happening in the midst of materials and technology developments including data storage and computational solutions such as the idea of virtual memory through to the first solar cells. 

    Kirby’s ICs went into an Air Force computer[ii] and an onboard guidance system for the Minuteman missile. He went on to help invent the first handheld calculator and thermal printer, both of which took advantage of progress in IC design to change our modern way of life[iii]

    TTL (transistor-to-transistor logic) circuitry was invented at TRW in 1961, they licensed it out for use in data processing and communications – propelling the development of modern computing. TTL circuits powered mainframes. Mainframes were housed in specialised temperature and humidity-controlled rooms and owned by large corporates and governments. Modern banking and payments systems rely on the mainframe as a concept. 

    AI’s early steps 

    Science Museum highlights

    What we now thing of as AI had been considered theoretically for as long as computers could be programmed. As semiconductors developed, a parallel track opened up to move AI beyond being a theoretical possibility. A pivotal moment was a workshop was held in 1956 at Dartmouth College. The workshop focused on a hypothesis ‘every aspect of learning or any other feature of intelligence can be so precisely described that a machine can be made to simulate it’. Later on, that year a meeting at MIT (Massachusetts Institute of Technology) brought together psychologists and linguists to discuss the possibility of simulating cognitive processes using a computer. This is the origin of what we’d now call cognitive science. 

    Out of the cognitive approach came some early successes in the move towards artificial intelligence[iv]. A number of approaches were taken based on what is now called symbolic or classical AI:

    • Reasoning as search – essentially step-wise trial and error approach to problem solving that was compared to wandering through a maze and back-tracking if a dead end was found. 
    • Natural language – where related phrases existed within a structured network. 
    • Micro-worlds – solving for artificially simple situations, similar to economic models relying on the concept of the rational consumer. 
    • Single layer neural networks – to do rudimentary image recognition. 

     By the time the early 1970s came around AI researchers ran into a number of problems, some of which still plague the field to this day:

    • Symbolic AI wasn’t fit for purpose solving many real-world tasks like crossing a crowded room. 
    • Trying to capture imprecise concepts with precise language.
    • Commonsense knowledge was vast and difficult to encode. 
    • Intractability – many problems require an exponential amount of computing time. 
    • Limited computing power available – there was insufficient intelligence per watt available for all but the simplest problems. 

    By 1966, US and UK funding bodies were frustrated with the lack of progress on the research undertaken. The axe fell first on a project to use computers on language translation. Around the time of the OPEC oil crisis, funding to major centres researching AI was reduced by both the US and UK governments respectively. Despite the reduction of funding to the major centres, work continued elsewhere. 

    Mini-computers and pocket calculators

    ICs allowed for mini-computers due to the increase in computing power per watt. As important as the relative computing power, ICs made mini-computers more robust, easier to manufacture and maintain. DEC (Digital Equipment Corporation) launched the first minicomputer, the PDP-8 in 1964. The cost of mini-computers allowed them to run manufacturing processes, control telephone network switching and control labouratory equipment. Mini-computers expanded computer access in academia facilitating more work in artificial life and what we’d think of as early artificial intelligence. This shift laid the groundwork for intelligence per watt as a guiding principle.

    A second development helped drive mass production of ICs – the pocket calculator, originally invented at Texas Instruments.  It demonstrated how ICs could dramatically improve efficiency in compact, low-power devices.

    LISP machines and PCs

    AI researchers required more computational power than mini-computers could provide, leading to the development of LISP machines—specialised workstations designed for AI applications. Despite improvements in intelligence per watt enabled by Moore’s Law, their specialised nature meant that they were expensive. AI researchers continued with these machines until personal computers (PCs) progressed to a point that they could run LISP quicker than LISP machines themselves. The continuous improvements in data storage, memory and processing that enabled LISP machines, continued on and surpassed them as the cost of computing dropped due to mass production. 

    The rise of LISP machines and their decline was not only due to Moore’s Law in effect, but also that of Makimoto’s Wave. While Gordon Moore outlined an observation that the number of transistors on a given area of silicon doubled every two years or so. Tsugio Makimoto originally observed 10-year pivots from standardised semiconductor processors to customised processors[v]. The rise of personal computing drove a pivot towards standardised architectures. 

    PCs and workstations extended computing beyond computer rooms and labouratories to offices and production lines. During the late 1970s and 1980s standardised processor designs like the Zilog Z80, MOS Technology 6502 and the Motorola 68000 series drove home and business computing alongside Intel’s X86 processors. 

    Personal computing started in businesses when office workers brought a computer to use early computer programmes like the VisiCalc spreadsheet application. This allowed them to take a leap forward in not only tabulating data, but also seeing how changes to the business might affect financial performance. 

    Businesses then started to invest more in PCs for a wide range of uses. PCs could emulate the computer terminal of a mainframe or minicomputer, but also run applications of their own. 

    Typewriters were being placed by word processors that allowed the operator to edit a document in real time without resorting to using correction fluid

    A Bicycle for the Mind

    Steve Jobs at Apple was as famous for being a storyteller as he was for being a technologist in the broadest sense. Internally with the Mac team he shared stories and memetic concepts to get his ideas across in everything from briefing product teams to press interviews. As a concept, a 1990 filmed interview with Steve Jobs articulates the context of this saying particularly well. 

    In reality, Jobs had been telling the story for a long time through the development of the Apple II and right from the beginning of the Mac. There is a version of the talk that was recorded some time in 1980 when the personal computer was still a very new idea – the video was provided to the Computer History Museum by Regis McKenna[vi].

    The ‘bicycle for the mind’ concept was repeated in early Apple advertisements for the time[vii] and even informed the Macintosh project codename[viii]

    Jobs articulated a few key concepts. 

    • Buying a computer creates, rather than reduces problems. You needed software to start solving problems and making computing accessible. Back in 1980, you programmed a computer if you bought one. Which was the reason why early personal computer owners in the UK went on to birth a thriving games software industry including the likes of Codemasters[ix]. Done well, there should be no seem in the experience between hardware and software. 
    • The idea of a personal, individual computing device (rather than a shared resource).  My own computer builds on my years of how I have grown to adapt and use my Macs, from my first sit-up and beg Macintosh, to the MacBook Pro that I am writing this post on. This is even more true most people and their use of the smartphone. I am of an age, where my iPhone is still an appendage and emissary of my Mac. My Mac is still my primary creative tool. A personal computer is more powerful than a shared computer in terms of the real difference made. 
    • At the time Jobs originally did the speech, PCs were underpowered for anything but data processing (through spreadsheets and basic word processor applications). But that didn’t stop his idea for something greater. 

    Jobs idea of the computer as an adjunct to the human intellect and imagination still holds true, but it doesn’t neatly fit into the intelligence per watt paradigm. It is harder to measure the effort developing prompts, or that expended evaluating, refining and filtering generative AI results. Of course, Steve Jobs Apple owed a lot to the vision shown in Doug Engelbart’s ‘Mother of All Demos’[x].

    Networks

    Work took a leap forward with office networked computers pioneered by Macintosh office by Apple[xi]. This was soon overtaken by competitors. This facilitated work flow within an office and its impact can still be seen in offices today, even as components from print management to file storage have moved to cloud-based services. 

    At the same time, what we might think of as mobile was starting to gain momentum. Bell Labs and Motorola came up with much of the technology to create cellular communications. Martin Cooper of Motorola made the first phone call on a cellular phone to a rival researcher at Bell Labs. But Motorola didn’t sell the phone commercially until 1983, as a US-only product called the DynaTAC 8000x[xii].  This was four years after Japanese telecoms company NTT launched their first cellular network for car phones. Commercial cellular networks were running in Scandinavia by 1981[xiii]

    In the same way that the networked office radically changed white collar work, the cellular network did a similar thing for self-employed plumbers, electricians and photocopy repair men to travelling sales people. If they were technologically advanced, they may have had an answer machine, but it would likely have to be checked manually by playing back the tape. 

    Often it was a receptionist in their office if they had one. Or more likely, someone back home who took messages. The cell phone freed homemakers in a lot of self-employed households to go out into the workplace and helped raise household incomes. 

    Fuzzy logic 

    The first mainstream AI applications emerged from fuzzy logic, introduced by Lofti A. Zadeh in 1965 mathematical paper. Initial uses were for industrial controls in cement kilns and steel production[xiv]. The first prominent product to rely on fuzzy logic was the Zojirushi Micom Electric Rice Cooker (1983), which adjusted cooking time dynamically to ensure perfect rice. 

    Rice Cooker with Fuzzy Logic 3,000 yen avail end june

    Fuzzy logic reacted to changing conditions in a similar way to people. Through the 1980s and well into the 1990s, the power of fuzzy logic was under appreciated outside of Japanese product development teams. In a quote a spokesperson for the American Electronics Association’s Tokyo office said to the Washington Post[xv].

    “Some of the fuzzy concepts may be valid in the U.S.,”

    “The idea of better energy efficiency, or more precise heating and cooling, can be successful in the American market,”

    “But I don’t think most Americans want a vacuum cleaner that talks to you and says, ‘Hey, I sense that my dust bag will be full before we finish this room.’ “

    The end of the 1990s, fuzzy logic was embedded in various consumer devices: 

    • Air-conditioner units – understands the room, the temperature difference inside-and-out, humidity. It then switches on-and-off to balance cooling and energy efficiency.
    • CD players – enhanced error correction on playback dealing with imperfections on the disc surface.
    • Dishwashers – understood how many dishes were loaded, their type of dirt and then adjusts the wash programme.
    • Toasters – recognised different bread types, the preferable degree of toasting and performs accordingly.
    • TV sets – adjust the screen brightness to the ambient light of the room and the sound volume to how far away the viewer is sitting from the TV set. 
    • Vacuum cleaners – vacuum power that is adjusted as it moves from carpeted to hard floors. 
    • Video cameras – compensate for the movement of the camera to reduce blurred images. 

    Fuzzy logic sold on the benefits and concealed the technology from western consumers. Fuzzy logic embedded intelligence in the devices. Because it worked on relatively simple dedicated purposes it could rely on small lower power specialist chips[xvi] offering a reasonable amount of intelligence per watt, some three decades before generative AI. By the late 1990s, kitchen appliances like rice cookers and microwave ovens reached ‘peak intelligence’ for what they needed to do, based on the power of fuzzy logic[xvii].

    Fuzzy logic also helped in business automation. It helped to automatically read hand-written numbers on cheques in banking systems and the postcodes on letters and parcels for the Royal Mail. 

    Decision support systems & AI in business

    Decision support systems or Business Information Systems were being used in large corporates by the early 1990s. The techniques used were varied but some used rules-based systems. These were used in at least some capacity to reduce manual office work tasks. For instance, credit card approvals were processed based on rules that included various factors including credit scores. Only some credit card providers had an analyst manually review the decision made by system.  However, setting up each use case took a lot of effort involving highly-paid consultants and expensive software tools. Even then, vendors of business information systems such as Autonomy struggled with a high rate of projects that failed to deliver anything like the benefits promised. 

    Three decades on, IBM had a similar problem with its Watson offerings, with particularly high-profile failure in mission-critical healthcare applications[xviii]. Secondly, a lot of tasks were ad-hoc in nature, or might require transposing across disparate separate systems. 

    The rise of the web

    The web changed everything. The underlying technology allowed for dynamic data. 

    Software agents

    Examples of intelligence within the network included early software agents. A good example of this was PapriCom. PapriCom had a client on the user’s computer. The software client monitored price changes for products that the customer was interested in buying. The app then notified the user when the monitored price reached a price determined by the customer. The company became known as DealTime in the US and UK, or Evenbetter.com in Germany[xix].  

    The PapriCom client app was part of a wider set of technologies known as ‘push technology’ which brought content that the netizen would want directly to their computer. In a similar way to mobile app notifications now. 

    Web search

    The wealth of information quickly outstripped netizen’s ability to explore the content. Search engines became essential for navigating the new online world. Progress was made in clustering vast amounts of cheap Linux powered computers together and sharing the workload to power web search amongst them.  As search started to trying and make sense of an exponentially growing web, machine learning became part of the developer tool box. 

    Researchers at Carnegie-Mellon looked at using games to help teach machine learning algorithms based on human responses that provided rich metadata about the given item[xx]. This became known as the ESP game. In the early 2000s, Yahoo! turned to web 2.0 start-ups that used user-generated labels called tags[xxi] to help organise their data. Yahoo! bought Flickr[xxii] and deli.ico.us[xxiii]

    All the major search engines looked at how deep learning could help improve search results relevance. 

    Given that the business model for web search was an advertising-based model, reducing the cost per search, while maintaining search quality was key to Google’s success. Early on Google focused on energy consumption, with its (search) data centres becoming carbon neutral in 2007[xxiv]. This was achieved by a whole-system effort: carefully managing power management in the silicon, storage, networking equipment and air conditioning to maximise for intelligence per watt. All of which were made using optimised versions of open-source software and cheap general purpose PC components ganged together in racks and operating together in clusters. 

    General purpose ICs for personal computers and consumer electronics allowed easy access relatively low power computing. Much of this was down to process improvements that were being made at the time. You needed the volume of chips to drive innovation in mass-production at a chip foundry. While application-specific chips had their uses, commodity mass-volume products for uses for everything from embedded applications to early mobile / portable devices and computers drove progress in improving intelligence-per-watt.

    Makimoto’s tsunami back to specialised ICs

    When I talked about the decline of LISP machines, I mentioned the move towards standardised IC design predicted by Tsugio Makimoto. This led to a surge in IC production, alongside other components including flash and RAM memory.  From the mid-1990s to about 2010, Makimoto’s predicted phase was stuck in ‘standardisation’. It just worked. But several factors drove the swing back to specialised ICs. 

    • Lithography processes got harder: standardisation got its performance and intelligence per watt bump because there had been a steady step change in improvements in foundry lithography processes that allowed components to be made at ever-smaller dimensions. The dimensions are a function wavelength of light used. The semiconductor hit an impasse when it needed to move to EUV (extreme ultra violet) light sources. From the early 1990s on US government research projects championed development of key technologies that allow EUV photolithography[xxv]. During this time Japanese equipment vendors Nikon and Canon gave up on EUV. Sole US vendor SVG (Silicon Valley Group) was acquired by ASML, giving the Dutch company a global monopoly on cutting edge lithography equipment[xxvi]. ASML became the US Department of Energy research partner on EUV photo-lithography development[xxvii]. ASML spent over two decades trying to get EUV to work. Once they had it in client foundries further time was needed to get commercial levels of production up and running. All of which meant that production processes to improve IC intelligence per watt slowed down and IC manufacturers had to start about systems in a more holistic manner. As foundry development became harder, there was a rise in fabless chip businesses. Alongside the fabless firms, there were fewer foundries: Global Foundries, Samsung and TSMC (Taiwan Semiconductor Manufacturing Company Limited). TSMC is the worlds largest ‘pure-play’ foundry making ICs for companies including AMD, Apple, Nvidia and Qualcomm. 
    • Progress in EDA (electronic design automation). Production process improvements in IC manufacture allowed for an explosion in device complexity as the number of components on a given size of IC doubled every 18 months or so. In the mid-to-late 1970s this led to technologists thinking about the idea of very large-scale integration (VLSI) within IC designs[xxviii]. Through the 1980s, commercial EDA software businesses were formed. The EDA market grew because it facilitated the continual scaling of semiconductor technology[xxix]. Secondly, it facilitated new business models. Businesses like ARM Semiconductor and LSI Logic allowed their customers to build their own processors based on ‘blocs’ of proprietary designs like ARM’s cores. That allowed companies like Apple to focus on optimisation in their customer silicon and integration with software to help improve the intelligence per watt[xxx]
    • Increased focus on portable devices. A combination of digital networks, wireless connectivity, the web as a communications platform with universal standards, flat screen displays and improving battery technology led the way in moving towards more portable technologies. From personal digital assistants, MP3 players and smartphone, to laptop and tablet computers – disconnected mobile computing was the clear direction of travel. Cell phones offered days of battery life; the Palm Pilot PDA had a battery life allowing for couple of days of continuous use[xxxi]. In reality it would do a month or so of work. Laptops at the time could do half a day’s work when disconnected from a power supply. Manufacturers like Dell and HP provided spare batteries for travellers. Given changing behaviours Apple wanted laptops that were easy to carry and could last most of a day without a charge. This was partly driven by a move to a cleaner product design that wanted to move away from swapping batteries. In 2005, Apple moved from PowerPC to Intel processors. During the announcement at the company’s worldwide developer conference (WWDC), Steve Jobs talked about the focus on computing power per watt moving forwards[xxxii]

    Apple’s first in-house designed IC, the A4 processor was launched in 2010 and marked the pivot of Makimoto’s wave back to specialised processor design[xxxiii].  This marked a point of inflection in the growth of smartphones and specialised computing ICs[xxxiv]

    New devices also meant new use cases that melded data on the web, on device, and in the real world. I started to see this in action working at Yahoo! with location data integrated on to photos and social data like Yahoo! Research’s ZoneTag and Flickr. I had been the Yahoo! Europe marketing contact on adding Flickr support to Nokia N-series ‘multimedia computers’ (what we’d now call smartphones), starting with the Nokia N73[xxxv].  A year later the Nokia N95 was the first smartphone released with a built-in GPS receiver. William Gibson’s speculative fiction story Spook Country came out in 2007 and integrated locative art as a concept in the story[xxxvi]

    Real-world QRcodes helped connect online services with the real world, such as mobile payments or reading content online like a restaurant menu or a property listing[xxxvii].

    I labelled the web-world integration as a ‘web-of-no-web’[xxxviii] when I presented on it back in 2008 as part of an interactive media module, I taught to an executive MBA class at Universitat Ramon Llull in Barcelona[xxxix]. In China, wireless payment ideas would come to be labelled O2O (offline to online) and Kevin Kelly articulated a future vision for this fusion which he called Mirrorworld[xl]

    Deep learning boom

    Even as there was a post-LISP machine dip in funding of AI research, work on deep (multi-layered) neural networks continued through the 1980s. Other areas were explored in academia during the 1990s and early 2000s due to the large amount of computing power needed. Internet companies like Google gained experience in large clustered computing, AND, had a real need to explore deep learning. Use cases include image recognition to improve search and dynamically altered journeys to improve mapping and local search offerings. Deep learning is probabilistic in nature, which dovetailed nicely with prior work Microsoft Research had been doing since the 1980s on Bayesian approaches to problem-solving[xli].  

    A key factor in deep learning’s adoption was having access to powerful enough GPUs to handle the neural network compute[xlii]. This has allowed various vendors to build Large Language Models (LLMs). The perceived strategic importance of artificial intelligence has meant that considerations on intelligence per watt has become a tertiary consideration at best. Microsoft has shown interest in growing data centres with less thought has been given on the electrical infrastructure required[xliii].  

    Google’s conference paper on attention mechanisms[xliv] highlighted the development of the transformer model. As an architecture it got around problems in previous approaches, but is computationally intensive. Even before the paper was published, the Google transformer model had created fictional Wikipedia entries[xlv]. A year later OpenAI built on Google’s work with the generative pre-trained transformer model better known as GPT[xlvi]

    Since 2018 we’ve seen successive GPT-based models from Amazon, Anthropic, Google, Meta, Alibaba, Tencent, Manus and DeepSeek. All of these models were trained on vast amounts of information sources. One of the key limitations for building better models was access to training material, which is why Meta used pirated copies of e-books obtained using bit-torrent[xlvii]

    These models were so computationally intensive that the large-scale cloud service providers (CSPs) offering these generative AI services were looking at nuclear power access for their data centres[xlviii]

    The current direction of development in generative AI services is raw computing power, rather than having a more energy efficient focus of intelligence per watt. 

    Technology consultancy / analyst Omdia estimated how many GPUs were bought by hyperscalers in 2024[xlix].

    CompanyNumber of Nvidia GPUs boughtNumber of AMD GPUs boughtNumber of self-designed custom processing chips bought
    Amazon196,0001,300,000
    Alphabet (Google)169,0001,500,000
    ByteDance230,000
    Meta224,000173,0001,500,000
    Microsoft485,00096,000200,000
    Tencent230,000

    These numbers provide an indication of the massive deployment on GPT-specific computing power. Despite the massive amount of computing power available, services still weren’t able to cope[l] mirroring some of the service problems experienced by early web users[li] and the Twitter ‘whale FAIL’[lii] phenomenon of the mid-2000s. The race to bigger, more powerful models is likely to continue for the foreseeable future[liii]

    There is a second class of players typified by Chinese companies DeepSeek[liv] and Manus[lv] that look to optimise the use of older GPT models to squeeze the most utility out of them in a more efficient manner. Both of these services still rely on large cloud computing facilities to answer queries and perform tasks. 

    Agentic AI

    Thinking on software agents went back to work being done in computer science in the mid-1970s[lvi]. Apple articulated a view[lvii]of a future system dubbed the ‘Knowledge Navigator’[lviii] in 1987 which hinted at autonomous software agents. What we’d now think of as agentic AI was discussed as a concept at least as far back as 1995[lix], this was mirrored in research labs around the world and was captured in a 1997 survey of research on intelligent software agents was published[lx]. These agents went beyond the vision that PapriCom implemented. 

    A classic example of this was Wildfire Communications, Inc. who created a voice enabled virtual personal assistant in 1994[lxi].  Wildfire as a service was eventually shut down in 2005 due to an apparent decline in subscribers using the service[lxii]. In terms of capability, Wildfire could do tasks that are currently beyond Apple’s Siri. Wildfire did have limitations due to it being an off-device service that used a phone call rather than an internet connection, which limited its use to Orange mobile service subscribers using early digital cellular mobile networks. 

    Almost a quarter century later we’re now seeing devices that are looking to go beyond Wildfire with varying degrees of success. For instance, the Rabbit R1 could order an Uber ride or groceries from DoorDash[lxiii]. Google Duplex tries to call restaurants on your behalf to make reservations[lxiv] and Amazon claims that it can shop across other websites on your behalf[lxv]. At the more extreme end is Boeing’s MQ-28[lxvi] and the Loyal Wingman programme[lxvii]. The MQ-28 is an autonomous drone that would accompany US combat aircraft into battle, once it’s been directed to follow a course of action by its human colleague in another plane. 

    The MQ-28 will likely operate in an electronic environment that could be jammed. Even if it wasn’t jammed the length of time taken to beam AI instructions to the aircraft would negatively impact aircraft performance. So, it is likely to have a large amount of on-board computing power. As with any aircraft, the size of computing resources and their power is a trade-off with the amount of fuel or payload it will carry. So, efficiency in terms of intelligence per watt becomes important to develop the smallest, lightest autonomous pilot. 

    As well as a more hostile world, we also exist in a more vulnerable time in terms of cyber security and privacy. It makes sense to have critical, more private AI tasks run on a local machine. At the moment models like DeepSeek can run natively on a top-of-the-range Mac workstation with enough memory[lxviii].  

    This is still a long way from the vision of completely local execution of ‘agentic AI’ on a mobile device because the intelligence per watt hasn’t scaled down to that level to useful given the vast amount of possible uses that would be asked of the Agentic AI model. 

    Maximising intelligence per watt

    There are three broad approaches to maximise the intelligence per watt of an AI model. 

    • Take advantage of the technium. The technium is an idea popularised by author Kevin Kelly[lxix]. Kelly argues that technology moves forward inexorably, each development building on the last. Current LLMs such as ChatGPT and Google Gemini take advantage of the ongoing technium in hardware development including high-speed computer memory and high-performance graphics processing units (GPU).  They have been building large data centres to run their models in. They build on past developments in distributed computing going all the way back to the 1962[lxx]
    • Optimise models to squeeze the most performance out of them. The approach taken by some of the Chinese models has been to optimise the technology just behind the leading-edge work done by the likes of Google, OpenAI and Anthropic. The optimisation may use both LLMs[lxxi] and quantum computing[lxxii] – I don’t know about the veracity of either claim. 
    • Specialised models. Developing models by use case can reduce the size of the model and improve the applied intelligence per watt. Classic examples of this would be fuzzy logic used for the past four decades in consumer electronics to Mistral AI[lxxiii] and Anduril’s Copperhead underwater drone family[lxxiv].  

    Even if an AI model can do something, should the model be asked to do so?

    AI use case appropriateness

    We have a clear direction of travel over the decades to more powerful, portable computing devices –which could function as an extension of their user once intelligence per watt allows it to be run locally. 

    Having an AI run on a cloud service makes sense where you are on a robust internet connection, such as using the wi-fi network at home. This makes sense for general everyday task with no information risk, for instance helping you complete a newspaper crossword if there is an answer you are stuck on and the intellectual struggle has gone nowhere. 

    A private cloud AI service would make sense when working, accessing or processing data held on the service. Examples of this would be Google’s Vertex AI offering[lxxv]

    On-device AI models make sense in working with one’s personal private details such as family photographs, health information or accessing apps within your device. Apps like Strava which share data, have been shown to have privacy[lxxvi] and security[lxxvii] implications. ***I am using Strava as an example because it is popular and widely-known, not because it is a bad app per se.***

    While businesses have the capability and resources to have a multi-layered security infrastructure to protect their data most[lxxviii]of[lxxix] the[lxxx] time[lxxxi], individuals don’t have the same security. As I write this there are privacy concerns[lxxxii] expressed about Waymo’s autonomous taxis. However, their mobile device is rarely out of physical reach and for many their laptop or tablet is similarly close. All of these devices tend to be used in concert with each other. So, for consumers having an on-device AI model makes the most sense. All of which results in a problem, how do technologists squeeze down their most complex models inside a laptop, tablet or smartphone? 


    [i] Radiomuseum – Loewe (Opta), Germany. Multi-system internal coupling 3NF

    [ii] (1961) Solid Circuit(tm) Semiconductor Network Computer, 6.3 Cubic inches in Size, is Demonstrated in Operation by U.S. Air Force and Texas Instruments (United States) Texas Instruments news release

    [iii] (2000) The Chip that Jack Built Changed the World (United States) Texas Instruments website

    [iv] Moravec H (1988), Mind Children (United States) Harvard University Press

    [v] (2010) Makimoto’s Wave | EDN (United States) AspenCore Inc.

    [vi] Jobs, S. (1980) Presentation on Apple Computer history and vision (United States) Computer History Museum via Regis McKenna

    [vii] Sinofsky, S. (2019) ‘Bicycle for the Mind’ (United States) Learning By Shipping

    [viii] Hertzfeld, A. (1981) Bicycle (United States) Folklore.org

    [ix] Jones, D. (2016) Codemasters (United Kingdom) Retro Gamer – Future Publishing

    [x] Engelbert, D. (1968) A Research Center For Augmenting Human Intellect (United States) Stanford Research Institute (SRI)

    [xi] Hormby, T. (2006) Apple’s Worst business Decisions (United States) OSnews

    [xii] Honam, M. (2009) From Brick to Slick: A History of Mobile Phones (United States) Wired

    [xiii] Ericsson History: The Nordics take charge (Sweden) LM Ericsson.

    [xiv] Singh, H., Gupta, M.M., Meitzler, T., Hou, Z., Garg, K., Solo, A.M.G & Zadeh, L.A. (2013) Real-Life Applications of Fuzzy Logic – Advances in Fuzzy Systems (Egypt) Hindawi Publishing Corporation

    [xv] Reid, T.R. (1990) The Future of Electronics Looks ‘Fuzzy’. (United States) Washington Post

    [xvi] Kushairi, A. (1993). “Omron showcases latest in fuzzy logic”. (Malaysia) New Straits Times

    [xvii] Watson, A. (2021) The Antique Microwave Oven that’s Better than Yours (United States) Technology Connections

    [xviii] Durbhakula, S. (2022) IBM dumping Watson Health is an opportunity to reevaluate artificial intelligence (United States) MedCity News

    [xix] (1998) PapriCom Technologies Wins CommerceNet Award (Israel) Globes

    [xx] Von Ahn, L., Dabbish, L. (2004) Labeling Images with a Computer Game (United States) School of Computing, Carnegie-Mellon University

    [xxi] Butterfield, D., Fake, C., Henderson-Begg, C., Mourachov, S., (2006) Interestingness ranking of media objects (United States) US Patent Office

    [xxii] Delaney, K.J., (2005) Yahoo acquires Flickr creator (United States) Wall Street Journal

    [xxiii] Hood, S., (2008) Delicious is 5 (United States) Delicious blog

    [xxiv] (2017) 10 years of Carbon Neutrality (United States) Google

    [xxv] Bakshi, V. (2018) EUV Lithography (United States) SPIE Press

    [xxvi] Wade, W. (2000) ASML acquires SVG, becomes largest litho supplier (United States) EE Times

    [xxvii] Lammers, D. (1999) U.S. gives ok to ASML on EUV effort (United States) EE Times

    [xxviii] Meade, C., Conway, L. (1979) Introduction to VLSI Systems (United States) Addison-Wesley

    [xxix] Lavagno, L., Martin, G., Scheffer, L., et al (2006) Electronic Design Automation for Integrated Circuits Handbook (United States) Taylor & Francis

    [xxx] (2010) Apple Launches iPad (United States) Apple Inc. website

    [xxxi] (1997) PalmPilot Professional (United Kingdom) Centre for Computing History

    [xxxii] Jobs, S. (2005) Apple WWDC 2005 keynote speech (United States) Apple Inc.

    [xxxiii] (2014) Makimoto’s Wave Revisited for Multicore SoC Design (United States) EE Times

    [xxxiv] Makimoto, T. (2014) Implications of Makimoto’s Wave (United States) IEEE Computer Society

    [xxxv] (2006) Nokia and Yahoo! add Flickr support in Nokia Nseries Multimedia Computers (Germany) Cision PR Newswire

    [xxxvi] Gibson, W. (2007) Spook Country (United States) Putnam Publishing Group

    [xxxvii] The O2O Business In China (China) GAB China

    [xxxviii] Carroll, G. (2008) Web Centric Business Model (United States) Waggener Edstrom Worldwide for LaSalle School of Business, Universitat Ramon Llull, Barcelona

    [xxxix] Carroll, G. (2008) Web of no web (United Kingdom) renaissance chambara

    [xl] Kelly, K. (2018) AR Will Spark the Next Big Tech Platform – Call It Mirrorworld (United States) Wired

    [xli] Heckerman, D. (1988) An Empirical Comparison of Three Inference Methods (United States) Microsoft Research

    [xlii] Sze, V., Chen, Y.H., Yang, T.J., Emer, J. (2017) Efficient Processing of Deep Neural Networks: A Tutorial and Survey (United States) Cornell University

    [xliii] Webber, M. E. (2024) Energy Blog: Is AI Too Power-Hungry for Our Own Good? (United States) American Society of Mechanical Engineers

    [xliv] Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., Polosukhin, I. (2017) Attention Is All You Need (United States) 31st Conference on Neural Information Processing Systems (NIPS 2017)

    [xlv] Marche, S. (2024) Was Linguistic A.I. Created By Accident? (United States) The New Yorker.

    [xlvi] Radford, A. (2018) Improving language understanding with unsupervised learning (United States) OpenAI

    [xlvii] Heath, N. (2025) Authors outraged to discover Meta used their pirated work to train its AI systems (Australia) ABC (Australian Broadcast Corporation)

    [xlviii] Morey, M., O’Sullivan, J. (2024) In-brief analysis: Data center owners turn to nuclear as potential energy source (United States) Today in Energy published by U.S. Energy Information Administration

    [xlix] Bradshaw, T., Morris, S. (2024) Microsoft acquires twice as many Nvidia AI chips as tech rivals (United Kingdom) Financial Times

    [l] Smith, C. (2025) ChatGPT’s viral image-generation upgrade is ruining the chatbot for everyone (United States) BGR (Boy Genius Report)

    [li] Wayner, P. (1997) Human Error Cripples the Internet (United States) The New York Times

    [lii] Honan, M. (2013) Killing the Fail Whale with Twitter’s Christopher Fry (United States) Wired

    [liii] Mazarr, M. (2025) The Coming Strategic Revolution of Artificial Intelligence (United States) MIT (Massachusetts Institute of Technology)

    [liv] Knight, W. (2025) DeepSeek’s New AI Model Sparks Shock, Awe, and Questions from US Competitors (United States) Wired

    [lv] Sharwood, S. (2025) Manus mania is here: Chinese ‘general agent’ is this week’s ‘future of AI’ and OpenAI-killer (United Kingdom) The Register

    [lvi] Hewitt, C., Bishop, P., Steiger, R. (1973). A Universal Modular Actor Formalism for Artificial Intelligence. (United States) IJCAI (International Joint Conference on Artificial Intelligence).

    [lvii] Sculley, J. (1987) Keynote Address On The Knowledge Navigator at Educom (United States) Apple Computer Inc.

    [lviii] (1987) Apple’s Future Computer: The Knowledge Navigator (United States) Apple Computer Inc.

    [lix] Kelly, K. (1995) Out of Control: The New Biology of Machines (United States) Fourth Estate

    [lx] Nwana, H.S., Azarmi, N. (1997) Software Agents and Soft Computing: Towards Enhancing Machine Intelligence Concepts and Applications (Germany) Springer

    [lxi] Rifkin, G. (1994) Interface; A Phone That Plays Secretary for Travelers (United States) The New York Times

    [lxii] Richardson, T. (2005) Orange kills Wildfire – finally (United Kingdom) The Register

    [lxiii] Spoonauer, M. (2024) The Truth about the Rabbit R1 – your questions answered about the AI gadget (United States) Tom’s Guide

    [lxiv] Garun, N. (2019) One year later, restaurants are still confused by Google Duplex (United States) The Verge

    [lxv] Roth, E. (2025) Amazon can now buy products from other websites for you (United States) The Verge

    [lxvi] MQ-28 microsite (United States) Boeing Inc.

    [lxvii] Warwick, G. (2019) Boeing Unveils ‘Loyal Wingman’ UAV Developed In Australia (United Kingdom) Aviation Week Network – part of Informa Markets

    [lxviii] Udinmwen, E. (2025) Apple Mac Studio M3 Ultra workstation can run Deepseek R1 671B AI model entirely in memory using less than 200W, reviewer finds (United Kingdom) TechRadar

    [lxix] Kelly, K. (2010) What Technology Wants (United States) Viking Books

    [lxx] Andrews, G.R. (2000) Foundations of Multithreaded, Parallel, and Distributed Programming (United States) Addison-Wesley

    [lxxi] Criddle, C., Olcott, E. (2025) OpenAI says it has evidence China’s DeepSeek used its model to train competitor (United Kingdom) Financial Times

    [lxxii] Russell, J. (2025) China Researchers Report Using Quantum Computer to Fine-Tune Billion Parameter AI Model (United States) HPC Wire

    [lxxiii] Mistral AI home page (France) Mistral AI

    [lxxiv] (2025) High-Speed Autonomous Underwater Effects. Copperhead (United States) Anduril Industries

    [lxxv] Vertex AI with Gemini 1.5 Pro and Gemini 1.5 Flash (United States) Google Cloud website

    [lxxvi] Untersinger, M. (2024) Strava, the exercise app filled with security holes (France) Le Monde

    [lxxvii] Nilsson-Julien, E. (2025) French submarine crew accidentally leak sensitive information through Strava app (France) Le Monde

    [lxxviii] Arsene, Liviu (2018) Hack of US Navy Contractor Nets China 614 Gigabytes of Classified Information (Romania) Bitdefender

    [lxxix] Wendling, M. (2024) What to know about string of US hacks blamed on China (United Kingdom) BBC News

    [lxxx] Kidwell, D. (2020) Cyber espionage for the Chinese government (United States) U.S. Air Force Office of Special Investigations

    [lxxxi] Gorman, S., Cole, A., Dreazen, Y. (2009) Computer Spies Breach Fighter-Jet Project (United States) The Wall Street Journal

    [lxxxii] Bellan, R. (2025) Waymo may use interior camera data to train generative AI models, but riders will be able to opt out (United States) TechCrunch

  • Pagers + more things

    Pagers

    Pagers went back into the news recently with Hizbollah’s exploding pagers. YouTuber Perun has done a really good run down of what happened.

    Based on Google Analytics information about my readership the idea of pagers might need an explanation. You’ve probably used a pager already, but not realised it yet.

    A Twosome Place wifi puck
    A restaurant pager from Korean coffee shop / dessert café A Twosome Place.

    For instance if you’ve been at a restaurant and given puck that brings when your table is ready, that’s a pager. The reason why its big it to prevent customers stealing them rather than the technology being bulky.

    On a telecoms level, it’s a similar principle but on a bigger scale. A transmitter sends out a signal to a particular device. In early commercial pagers launched in the 1960s such as the ‘Bellboy’ service, the device made a noise and you then got to a telephone, phoned up a service centre to receive a message left for you. Over time, the devices shrunk from something the size of a television remote control to even smaller than a box of matches. The limit to how small the devices got depended on display size and battery size. You also got displays that showed a phone number to call back.

    By the time I had a pager, they started to get a little bigger again because they had displays that could send both words and numbers. These tended to be shorter than an SMS message and operators used shortcuts for many words in a similar way to instant messaging and text messaging. The key difference was that most messages weren’t frivolous emotional ‘touchbases’ and didnt use emojis.

    Beepers
    A Motorola that was of a similar vintage to the one I owned.

    When I was in college, cellphones were expensive, but just starting to get cheaper. The electronic pager was a good half-way house. When I was doing course work, I could be reached via my pager number. Recruiters found it easier to get hold of me, which meant I got better jobs during holiday time as a student.

    I moved to cellphone after college when I got a deal at Carphone Warehouse. One Motorola Graphite GSM phone which allowed two lines of SMS text to be displayed. I had an plan that included the handset that cost £130 and got 12 months usage. For which I got a monthly allowance of 15 minutes local talk time a month.

    I remember getting a call about winning my first agency job, driving down a country road with the phone tucked under my chin as I pulled over to take the call. By this time mobile phones were revolutionising small businesses with tradesmen being able to take their office with them.

    The internet and greater data speeds further enhanced that effect.

    Pagers still found their place as communications back-up channel in hospitals and some industrial sites. Satellite communications allowed pagers to be reached in places mobile networks haven’t gone, without the high cost of satellite phones.

    That being said, the NHS are in the process of getting rid of their pagers after COVID and prior to COVID many treatment teams had already moved to WhatsApp groups on smartphones. Japan had already closed down their last telecoms pager network by the mid-2010s. Satellite two-way pagers are still a niche application for hikers and other outward bound activities.

    Perun goes into the reasons why pagers were attractive to Hesbollah:

    • They receive and don’t transmit back. (Although there were 2-way pager networks that begat the likes of the BlackBerry device based on the likes of Ericsson’s Mobitex service.)
    • The pager doesn’t know your location. It doesn’t have access to GNSS systems like GPS, Beidou, Gallileo or GLONASS. It doesn’t have access to cellular network triangulation. Messages can’t transmit long messages, but you have to assume that messages are sent ‘in the clear’ that is can be read widely.

    Consumer behaviour

    Yes, CEOs are moving left, but ‘woke capitalism’ is not the whole story | FT

    Culture

    ‘We were cheeky outlaws getting away with it’: the total euphoria of Liverpool’s 90s club scene | The Guardian – maybe one day I will tell my side of this tale. It’s all a bit more nuanced and I was stone cold sober throughout it all, which is a rare perspective.

    Economics

    Invest 2035: the UK’s modern industrial strategy – GOV.UK

    Corporate Germany is on sale | FT

    Health

    Ukraine’s pioneering virtual reality PTSD therapy | The Counteroffensive

    Korea

    The sabukaru Guide to Seoul’s PC Room Culture | Sabukaru

    Luxury

    How luxury priced itself out of the market | FT – brands have tested the elasticity of pricing and pushed beyond the limits for their middle class customer base

    Watch-maker Jaeger-LeCoultre expands into fragrances inspired by its Reverso dress watches: Jaeger-LeCoultre fragrances take form | Luxury Daily

    Ozempic is transforming your gym | FT, The Vogue Business Spring/Summer 2025 size inclusivity report | Vogue Business – GLP-1s blamed for stalled progress.

    Ferrari, Hermès lead global luxury brand growth in 2024: Interbrand | Luxury Daily

    What is Chinese style today? | Vogue Businessstreet style at Shanghai Fashion Week has been low-key. The bold looks of the past have given way to a softer aesthetic that’s more layered and feminine, with nods to Chinese culture and history. This pared-back vibe was also found on the runways. Part of this might be down to a policy led movement against conspicuous consumption typified by Xi Jinping’s ‘common prosperity‘.

    Marketing

    Adland’s talent spill: Seniors double blocked as ageism, cost-cutting compounded by ‘threatened’ younger managers | Mi3

    Where to start with multisensory marketing | WARC – 61% of consumers looking for brands that can “ignite intense emotions”. Immersive experiences that are holistic tap into people’s emotions and linger in the memory. It’s also an opportunity for using powerful storytelling to communicate a brand story.

    Media

    Tesco to launch location-based self-scanner adverts in stores – Retail Gazette

    Everyone is burning out on the news, including journalists – Baekdal

    Online

    Roblox: Inflated Key Metrics For Wall Street And A Pedophile Hellscape For Kids – Hindenburg Research

    How Google Influences Public Opinion | HackerNoon

    Software

    Apple macOS 15 Sequoia is officially UNIX • The Register

    Web-of-no-web

    Airbus to cut 2500 staff in Space Systems | EE News Europe“In recent years, the defence and space sector and, thus, our Division have been impacted by a fast changing and very challenging business context with disrupted supply chains, rapid changes in warfare and increasing cost pressure due to budgetary constraints,” said Mike Schoellhorn, CEO of the Airbus Defence and Space business.

    Wireless

    Boeing plans quantum satellite | EE News Europe

    Elon Musk battles Indian billionaires over satellite internet spectrum | FT

  • Dogfight by Fred Vogelstein

    The story Dogfight tells feels much more recent than it now is almost two decades on, and yet so far away as smartphones are central to our lives. Back in the mid and late 2000s Silicon Valley based journalist Fred Vogelstein was writing for publications like Wired and Fortune at the time Apple launched the iPhone and Google launched Android. He had a front-row seat to the rivalry between the two brands.

    Dogfight

    And being on the ground in Silicon Valley would have meant that he would have had access to scuttlebutt given in confidence of anonymity as well as official media access.

    But he’s probably best known for being part of the story itself: Fred Vogelstein wrote about his experiences with Microsoft’s PR machine for Wired back in 2007.

    The fight

    Original iPhone - The Motorola ROKR
    The Motorola ROKR E1 I was given, but eventually threw out.

    Dogfight starts some time after Apple had withdrawn support for Motorola’s ROKR phone, which was able to sync with iTunes for music downloads. This particular track of Apple’s history isn’t really documented in Dogfight.

    The book goes through two separate but entangled story strands. The first is Apple’s development of the Apple iPhone and iPad. At that time Apple in the space of a decade had gone from almost going under, to having the iPod and iTunes music store, together with a resuscitated computer range thanks to the iMac and Mac OS X.

    The Google of this era was at its peak, search had become a monopoly and the company was overflowing with wondrous and useful web services from Google Earth to Google Reader. What was less apparent was that inside Google was chaos due to internal politics and massive expansion. Into this walked Andy Rubin who had built and designed the Danger Hiptop, sold exclusively on T-Mobile as the Sidekick.

    T-Mobile Sidekick2 w/ skin

    The Sidekick had been a text optimised mobile device. It featured email, instant messaging and SMS text messages. His new company Android had been acquired by Google to build a new type of smartphone that would continue to provide a mobile audience for Google services.

    Dogfight’s style

    Dogfight is undemanding to read but doesn’t give insight in the way that other works like Insanely Great, Where Wizards Stay Up Late and Accidental Empires did. Part of this might be down to the highly orchestrated public relations campaigns happening at the time.

    Instead Vogelstein documents developments, from video recordings, marketing materials and court documents. Some of the things covered were items that I had largely forgotten about like music labels launching albums as multimedia apps on the new iPhone ecosystem. This was doing in software with what the Claudia Schiffer Palm Vx or the U2 autograph edition iPod had previously done in hardware.

    U2 iPod (front)

    Google’s decision to ‘acquihire’ the Android team to build their mobile operating system, wasn’t examined in depth. Yet there are clear parallels with the Boca Raton team in IBM which came up with the IBM PC a quarter of a century earlier. Vogelstein kept to the facts.

    It’s a workman-like if uninspiring document. And that mattered deeply to me. Part of the reason why I went into agency life was because I was inspired about the possibility of working the technology sector. This inspiration had been fired up by the chutzpah and pioneering spirit portrayed in older technology of history books. Some of them were flawed characters, but all of them had an energy and vibrancy to make the world a better place.

    Wired magazine issues had a similar effect. Yet in Dogfight Vogelstein brought neither of those influences to the table, instead he was writing an account that will probably only read by academics citing his material as a contemporary account in a future thesis.

    Dogfight isn’t the Liar’s Poker of the smartphone world, it isn’t even that illuminating about the nature of Silicon Valley.

    This is probably why Vogelstein hasn’t had a book published since Dogfight – he’s a reporter, not a writer. You can find more book reviews here.

  • SCART + more things

    SCART

    I had used SCART for a long time. The large parallel port plugs and stiff coaxial cables that looked as if they were limbs that had fallen of a cyberpunk twisted oak, were just part of the living room. Even if you hadn’t looked behind the TV cabinet, you maybe seen them as part of the flight cased TV and laser disc combo back when karaoke first took off as an activity in your local pub. Or the connection between a pub’s TV for Sky Sports and the set-top box held up high on the pub wall for punters to enjoy the game with their drink.

    That was up until their replacement by HDMI cables, TOSLINK and ethernet cables in my home TV set-up over the past ten years. SCART was actually the name of the French radio and television makers association who developed the standard back in the mid-1970s. SCART came along as TVs were becoming more reliable and one started to see the decline of the TV rental market.

    My parents first TV that they bought in the UK was a HMV-branded set with glowing vacuum tubes in the back despite a relatively modern looking TV case with push buttons similar to this one. SCART came along just a few years later.

    A lot of the SCART features assumed that consumers would move to larger TVs with better displays and sound that would come to dominate the living room of European homes. And they were right, though through much of the 1980s many homes still had a 13″ colour portable TV.

    SCART became compulsory for televisions sold in France from 1980 onwards. The standard was sufficiently robust and scalable for it to be used in transmitting 1080p high definition video as HDMI came to prominence. France eventually revoked their compulsory adoption of SCART in 2015.

    Things that we take as standard on HDMI like using the VCR, set-top box or disc player to turn on the TV, were also standard on SCART from the late 1970s. You could daisy chain equipment together, which was important for people who were early adopters of satellite receivers, cable TV boxes and laser disc players.

    SCART came at a time when globalisation moved the gravity of consumer electronics further east. First to Japan, then Taiwan, Hong Kong, South Korea, Malaysia and eventually China. Brands like Philips, Grundig, Nokia, Nordmende, Thomson and Ferguson were swept to the side by likes of Sony, Mitsubishi, Panasonic, Sharp, LG and Samsung.

    The SCART socket and plug were clever designs. You could only put them in the right way around and for something with 21 pins in they were not only robust but easy to plug and plug out again. Though once you had a SCART connection set up, you left it well alone.

    China

    Over 75% of foreign money invested into Chinese stocks in 2023 has left | FT

    Nvidia investors weigh risks from US’s China chip rules ahead of earnings | FT

    China’s property crisis is stirring protests across the country – Nikkei AsiaAround 50 to 70 demonstrations are now occurring monthly, though August saw about 100 worker-led protests, three times as many as the same month a year earlier. Since June 2022, demonstrations have occurred in 276 cities nationwide. The protests have been somewhat concentrated in wealthier cities, particularly Shenzhen, Xi’an and Zhengzhou, and together have involved tens of thousands of people.

    Consumer behaviour

    Inside the Cabbage Patch Kids frenzy and Black Friday riots of 1983 | Fast Company

    Gen Z Subcultures | Horizon Catalyst

    Culture

    How Liverpool’s legendary Club 051 was brought back from the brink of demolition – Features – Mixmag“The nightclub in itself is a thing of the past,” he continues. “Most of the stuff people class as nightclubs now are bars or bar-restaraunts that have DJs playing in there and it’s booze culture. There is industrial clubs, especially in London – but in Liverpool, there isn’t really any.” It’s difficult to disagree with Lee, being in this space with its pillars and it’s expansive-yet-intimate atmosphere feels markedly different to being in the kind of modern venues that tend to be of a similar capacity in the UK — converted warehouses and industrial spaces, with a routine approach of sticking decks and the end of the room alongside the soundsystem and a bar at the back

    Design

    Language Log » Eddie Bauer – young people either can’t read or don’t want cursive fonts according to this Eddie Bauer rebrand

    Finance

    Orange introduces its super-app, Max it, to simplify everyday life for people in Africa and the Middle East  – Newsroom Orange Groupe

    Binance chief Changpeng Zhao resigns after US guilty plea | FT

    Gadgets

    First camera that uses C2PA to assure the fidelity of the images taken: Leica M11-P | Leica Camera AG more here: ongoing by Tim Bray · On C2PA

    Health

    As Hong Kong’s elderly face loneliness epidemic, carers hope dogs and disco will keep post-Covid isolation at bay – Hong Kong Free Press HKFP

    Men May Die Quicker, but Women Don’t Have to Get Sicker | Muse by Clio – great content on better health for women. The reality is that men DO die quicker and a good deal of it doesn’t need to happen either – Men, Health, Life Expectancy, and Healthy Changes | Lifespan

    Novo rations Ozempic starter kits amid surge in use for weight loss | Reuters

    Hong Kong

    Plight of workless Hongkongers in the UK reveals a skills mismatch | FT

    Luxury

    Quiet fashion sweeps China as economy cools | Jing Daily

    Maison Margiela just dropped a hot haute couture flip phone | Dazed – harking back to the early 2000s when Prada had a co-branded phone with LG and Motorola did a special gold Dolce & Gabanna branded RAZR handset.

    Case Study | Fashion’s New Rules For Sports Marketing | BoFWhen the Paris Olympic and Paralympic Games kick off in July 2024, the millions of global fans watching will see far more than just athletes. LVMH brands such as Louis Vuitton, Dior and Berluti will provide uniforms for select teams, while the medals will be the work of its high jewellery label, Chaumet. For the first time ever, the games will feature LVMH-sponsored athletes, including world-champion swimmer Léon Marchand, European champion in artistic gymnastics Mélanie de Jesus dos Santos and Olympic gold-medalist fencer Ezno Lefort. The “premium” partnership between LVMH and the Olympics marks the biggest indication to date of sport’s newfound importance to fashion. Until recently, sport was one of the remaining cultural arenas in which fashion, with a few exceptions, had failed to forge long-lasting and meaningful relationships. That has changed. Fashion brands are waking up to the commercial value of sports like basketball, football, tennis and Formula 1 as they look to be part of the booming sports-sponsorship market, which is projected to grow from $63.1 billion in 2021 to $109.1 billion by 2030, according to PwC.

    What Antoine Arnault’s departure from Berluti could mean for LVMH | Vogue Business

    Decoding China’s young luxury watch consumer | Vogue Business

    Marketing

    Revealed: how top PR firm uses ‘trust barometer’ to promote world’s autocrats | US news | The Guardian – the reality is that its more of a door-opener a la McKinsey rather than reputation washing Middle Eastern governments

    Why the future of Planning is Opera, Only Fans, God, and Low Traffic Neighbourhoods

    Modelling short-and long-term marketing effects in the consumer purchase journey – ScienceDirect – rituals can increase repeat purchase

    Materials

    Ford Walks Fine Line as It Builds Gigafactory—With CATL – EE Times and Ambarella CEO: ‘Chinese OEMs Are Copying the Tesla Model’ – EE Times

    Media

    Survey reveals surprising age trend among paid subscribers of electronic comics in Japan | SoraNews24an Internet survey conducted by Oricon ME between May 17 and June 7 of this year revealed. According to 10,438 e-comic reader respondents between the ages of 15-79 who read e-comics at least once per week, the age demographic that subscribed most frequently for these services, at 50.5 percent, was those in their 50s. Conversely, the age group that subscribed least frequently, at 6.2 percent, was those between 10 to 19 years old.

    Can Hong Kong libraries win back readers? Public facilities try every trick in the book to lose ‘boring’ label amid rise of e-texts, pandemic habits | South China Morning PostLibraries are struggling to woo visitors despite pulling out the stops with new offerings, including more open areas and digital services. Residents made 18 million visits to public libraries in first 10 months of year, well below 34.7 million recorded for whole of 2019 – censorship related to the National Security law and the departure of young middle class professionals won’t have helped either. More Hong Kong-related content here.

    WPP Open X Opens Up On Coca-Cola Partnership, Which Is Fizzing Away Nicely After 2 Years | The Drum

    DouYu CEO Chen Shaojie arrested in latest executive crackdown in China | CNN Business – DouYu is kind of similar to Twitch

    Online

    Singing from the CCP’s songsheet | Australian Strategic Policy Institute | ASPI

    The FT on how life is getting increasingly difficult for the creator economy

    Retailing

    Amazon newsroom: Hyundai and Amazon Partner to Deliver Innovative Customer Experiences and Cloud Transformation

    Security

    “Here to stay” – Chinese state-affiliated hacking for strategic goals | Merics

    Israel Arms the World’s Autocrats—With Weapons Tested on Palestinians | The New Republic“It’s either the civil rights in some country or Israel’s right to exist,” said Eli Pinko, the former head of Israel’s Defense Export Control Agency, in 2021. “I would like to see each of you face this dilemma and say: ‘No, we will champion human rights in the other country.’” Under this ethos, the Israeli economy quickly “abandoned oranges for hand grenades,” as one critic memorably quipped. After the Six-Day War in 1967, when the 19-year-old nation launched a preemptive strike on its neighbors—taking over the West Bank, Gaza, East Jerusalem, and the Golan Heights—a new era in Israeli politics began

    The Russian Way of War | Foreign AffairsRussia has long been home to creative thinking in both conventional and nonconventional warfare. In the conventional arena, during the 1920s and 1930s, Soviet military thinkers generated novel ideas such as the concept of deep battle—breaking through enemy lines and creating a continuous moving front. These ideas shaped, and continue to shape, NATO thinking. In the unconventional space, Soviet influence was even more profound. From its founding days, Soviet leaders developed a body of ideas and practices about subversive conflict, including forging documents, co-opting agents abroad, and establishing disinformation campaigns. An early example was the groundbreaking Operation Trest. Carried out in the 1920s, Trest operatives established fictitious underground political cells in Europe in the 1920s to infiltrate anti-Bolshevik groups and lure their members back to the Soviet Union.

    Secretive White House Surveillance Program Gives Cops Access to Trillions of US Phone Records | WIREDThe DAS program, formerly known as Hemisphere, is run in coordination with the telecom giant AT&T, which captures and conducts analysis of US call records for law enforcement agencies, from local police and sheriffs’ departments to US customs offices and postal inspectors across the country, according to a White House memo reviewed by WIRED. Records show that the White House has provided more than $6 million to the program, which allows the targeting of the records of any calls that use AT&T’s infrastructure—a maze of routers and switches that crisscross the United States. In a letter to US attorney general Merrick Garland on Sunday, Wyden wrote that he had “serious concerns about the legality” of the DAS program, adding that “troubling information” he’d received “would justifiably outrage many Americans and other members of Congress.” That information, which Wyden says the DOJ confidentially provided to him, is considered “sensitive but unclassified”

    Software

    Microsoft’s Copilot AI Rises From the Ashes of Bob and Clippy

    Doomer vs Accelerationist: the two tribes fighting for the future of AI | Dazed and The ‘AI doomers’ have lost this battle | FT on the outcome of OpenAI and its likely pivot towards a neo-liberal hell-for-leather charge to singularity. Whether they will get there is a bigger question, I have my doubts – Garden Pathing AI – by Erik J Larson – Colligo – LLMs are a technological dead end

    How does Stable Diffusion work?

    Style

    Why have people looked the same for the last 20 years? | Dazed

    Following the Silk Road, Les Benjamins readies for global expansion | Vogue Business

    Technology

    How Micro-AUVs Are Revolutionizing Ocean Exploration – EE Times

    Wireless

    Consumer Cellular’s Iris Flip isn’t just your grandma’s dumb phone | Fast Company

  • General Magic

    General Magic has a reputation of being the technology equivalent of the Jordan-era Chicago Bulls, but it ended up going nowhere. I never got to see the device in person, it was only available in Japan and the US. It’s as famous much for its alumni, as it is for its commercial failure.

    Apple "Paradigm" project/General Magic/Sony "Magic Link" PDA

    This is captured in a documentary of the same name. For students of Silicon Valley history and Apple fan boys – the team at General Magic sounds like a who’s who of the great and the good in software development and engineering.

    General Magic started within Apple with a brief that sounds eerily like what I would have expected for the iPhone decades later.

    “A tiny computer, a phone, a very personal object . . . It must be beautiful. It must offer the kind of personal satisfaction that a fine piece of jewelry brings. It will have a perceived value even when it’s not being used… Once you use it you won’t be able to live without it.”

    Sullivan M. (July 26, 2018) “General Magic” captures the legendary Apple offshoot that foresaw the mobile revolution. (United States) Fast Company magazine

    The opening sequence tells you what the documentary is going to lay out. Over carefully curate images of Silicon Valley campuses, Segway riders and the cute bug like Google autonomous vehicle a voice talks about success and failure. That failure is part of the process of development. That General Magic has a legendary status due to its status as precursor to our always-on modern world and while the company failed, the ideas didn’t.

    Autonomous cars aren't nearly as clever as you think, says Toyota exec - Computerworld

    The genesis of the spirit of General Magic goes back to the development and launch of the Macintosh with its vision of making computers accessible. The team looked around the next thing that would have a similar vision and impact of a product. The Mac had got some of these developers on the front cover of Rolling Stone – they were literally rockstars.

    You get a tale of dedication and excitement that revolved around a pied piper type project lead Marc Porat, who managed to come to the table with a pretty complete vision and concept of where General Magic (and the world) would be heading. The archive of footage of the offices with its cool early to mid 1990s Apple Office products still amazes now. The look of the people in the archive footage, make my Yahoo! colleagues a decade later seem corporate and uptight by comparison.

    Veteran journalist Kara Swisher said that she started following the company because it was ‘the start of mobile computing, this is where it leads’.

    What sets the documentary apart is that it tapped into footage shot by film maker David Hoffman who was hired to capture the product development process. The protagonists then provide a voice over of their younger selves. Their idealism reaches back to the spirit of the 1960s. You can see how touch screen screens and the skeuomorphic metaphors were created and even animate emoticons.

    I’ve never known a development process with so much documentary footage. Having been in this process on the inside, the General Magic documentary portrays a process and dynamics that haven’t changed that much.

    The ecosystem that the startup assembled including AT&T, Apple, Motorola and Sony made sense given the ecosystem and power that Microsoft had behind it. It’s hard to explain how dominant and aggressive Microsoft was in the technology space. Newton came out as a complete betrayal and John Sculley, who is interviewed in the documentary comes across worse than he would have liked.

    The documentary also has access to the 1994 promotional film where General Magic publicly discussed the concept of ‘The Cloud’ i.e. the modern web infrastructure – but the documentary doesn’t dwell on this provable claim.

    Goldman Sachs was a key enabler, the idea of the concept IPO set the precedent for Netscape, Uber, WeWork and the 2020s SPAC fever.

    In a time when there is barely one thing changing the technology environment, General Magic were pursuing their walled garden of their private cloud and missed the web for a while. Part of this is down to their relationship with AT&T.

    The documentary covers how project management dogged the project. Part of the problem was perfectionism was winning over the art of the possible and not focusing on the critical items that needed to be done. The panic of having to ship.

    It’s about getting the balance between ‘move fast and break things’ versus crafting a jewel of a product.

    But shipping wasn’t enough, the execution of shopper marketing and sales training was a disaster. The defeat was hard given the grand vision. But the ultimate lesson is that YOU are not representative of the mainstream market.

    The documentary post-mortem featuring thinkers like Kara Swisher and Paul Saffo points out the lack of supporting infrastructure, that would take years to catch up to where General Magic’s Magic Link had gone. Paul Saffo uses a surfing analogy that I had previously read in Bob Cringely’s Accidental Empires about catching the right wave at the right time.

    John Sculley over at Apple made similar mistakes to the General Magic team which resulted in him being fired from Apple. Sculley makes the very human admission that being fired from Apple took him about 15 years to recover from personally.

    IBM Simon

    The documentary gives a lot of the credit (maybe too much of it) to General Magic as the progenitor of what we now think of as smartphones. The reality as with other inventions is that innovation has its time and several possible ‘inventors’; or what author Kevin Kelly would call ‘the technium’. This is the idea that technological progression is inevitable and that it stands on the layers of what has gone before, like fossils found inside rocks several foot deep. For instance, IBM created a device called Simon which was ‘smartphone’ which sold about 50,000 units to BellSouth customers in the six months it was on the market. Motorola – who were a General Magic partner also launched a smartphone version of the Apple Newton called the Motorola Marco in January 1995 and there are more devices around the same time.

    Reality is messy and certainly not like the clean direct line that the General Magic documentary portrays, even the Newton was only part of the story.

    The Wonder Years

    I was thinking about what I liked so much about the General Magic documentary. I immediately thought about it reminding me of my falling in love with the nascent internet and technology, which then bought me to the start of my agency career working with Palm (the company that eventually helped kill off General Magic’s product ambitions) and the Franklin REX which came out of sychronisation pioneers Starfish Software.

    But it was deeper than that. The Silicon Valley portrayed in the General Magic documentary wasn’t the dystopian hellscape of platform firms, generation rent, toxic tech bro culture and ‘churn and burn’ HR culture. Instead the General Magic documentary story represented a halcyon past of Silicon Valley portrayed in books like Where Wizards Stay Up Late, Fire In The Valley and Insanely Great. Where talented people motivated by a fantastic vision thing, with a user centred mission worked miracles. The darkness of fatigue and god knows what else is largely hidden by a Wonder Years TV show feel good nostalgia. Maybe it gives us hope again in the tech sector, despite Peter Thiel, Mark Zuckerberg, Tim Cook and Elon Musk? Maybe that hope might inspire something great again?

    Marc Porat’s personal tragedy and Tony Fadell’s business failure brings a hint of the real world through the door. The documentary uses Fadell’s link with the iPod and iPhone as a point of redemption, resilience, perseverance and vindication for General Magic.

    There’s also a cautionary tale full of lessons learned for new entrepreneurs, who often get the vision thing but forget about the details. More on General Magic here.

    More reviews here.