The online field has been one of the mainstays since I started writing online in 2003. My act of writing online was partly to understand online as a medium.
Online has changed in nature. It was first a destination and plane of travel. Early netizens saw it as virgin frontier territory, rather like the early American pioneers viewed the open vistas of the western United States. Or later travellers moving west into the newly developing cities and towns from San Francisco to Los Angeles.
America might now be fenced in and the land claimed, but there was a new boundless electronic frontier out there. As the frontier grew more people dialled up to log into it. Then there was the metaphor of web surfing. Surfing the internet as a phrase was popularised by computer programmer Mark McCahill. He saw it as a clear analogue to ‘channel surfing’ changing from station to station on a television set because nothing grabs your attention.
Web surfing tapped into the line of travel and 1990s cool. Surfing like all extreme sport at the time was cool. And the internet grabbed your attention.
Broadband access, wi-fi and mobile data changed the nature of things. It altered what was consumed and where it was consumed. The sitting room TV was connected to the internet to receive content from download and streaming services. Online radio, podcasts and playlists supplanted the transistor radio in the kitchen.
Multi-screening became a thing, tweeting along real time opinions to reality TV and live current affairs programmes. Online became a wrapper that at its worst envelopes us in a media miasma of shrill voices, vacuous content and disinformation.
YouTuber aini does good videos that analyse sociological and cultural subjects, so a video on East Asian beauty standards was inevitable. East Asian beauty standards are even more important now due to the cultural impact that they have:
Korean and Japanese beauty products that have become popular from BB cream to SK-II
Filter / camera effects mobile apps – you can see their influence looking at how Cardi B does her make-up
Soft power assets: Hallyu and anime popularity – it affects the aesthetics of this content
China
Huawei building automotive ecosystem without making its own cars – Huawei will not build cars on its own, but will continue to strengthen its automotive ecosystem alliance and platform, integrating R&D efforts of related carmakers to provide diverse resources of smart systems, software, chips and other aspects – interesting profile by Taiwanese technology news outlet DigiTimes
Interesting that proposes that cyberpunk owes as much to Japanese psyche during late bubble Japanese miracle culture as opposed to the writings of American authors Bruce Sterling and William Gibson. It reflects angst, consumerism and accelerated technology.
Cybersecurity Label for U.S. Coming as Early as April – EE Times – 600-plus companies that have joined the ioXt Alliance to help it build confidence in Internet of Things products will be among the first to experience the national cybersecurity label NIST is developing for consumer Internet of Things (IoT) products and consumer software products—as soon as April
Why The Chinese Balloon Was a Necessary Wake-Up Call – Recent events have shown that terrorism is not the only threat to the U.S. homeland. Moscow’s invasion of Ukraine shattered not only the 75-year peace in Europe but also Americans’ sense of security, particularly when the Kremlin has threatened nuclear escalation. Relations with Beijing have also deteriorated to a 40-year low, punctuated by the threat of Chinese aggression against Taiwan and other regional allies and covert activities within the United States
I don’t care that much about the comings and goings of the Royal Family, let alone minor players like Harry and Meghan. I am a citizen of a republic not a subject of the Windsors. I can remember watching the first wedding of Princess Anne on our black and while television. But beyond the sound of the wedding march; I really didn’t have much of a clue of what was going on. My Mam went around the kitchen doing what she needed to be done. This was on in the background, but didn’t feel important.
By comparison, watching the state funeral Eamon de Valera; had much more of an impact. I could feel the seriousness of my grandparents and my Uncle who lived on the family farm watching the procession of the flag-draped coffin through Dublin to Glasnevin cemetery.
I have been vaguely aware of controversy surrounding Harry and Meghan, but not the detail. I know, that if I asked, my Mum would be able to give me a blow-by-blow account while my Dad would roll his eyes. If you’d have asked me three months ago if I would have been writing part of a post focusing on Harry and Meghan, I would have expressed a strong doubt.
South Park
That all changed when they saw South Park’s episode about Harry and Meghan’s ‘worldwide privacy tour’. It seemed to be a lightning rod for their collective doubts about the couple. I then had to give them a crash course on the cultural relevance of South Park. Hong Kong friends didn’t ask about Harry and Meghan, but instead asked why South Park used Harry and Meghan to pick on Canada?
Political theorist and author Francis Fukuyama wrote one of the mis-understood books of the late 20th century. The End of History (And The Last Man) was written in 1989 and the title and Francis Fukuyama have been misquoted endlessly since.
At the 2020 Munich Security Conference Francis Fukuyama gave a talk about the book and what it actually meant from his perspective.
This one on tribalism on and populism is also very interesting.
Business
Great video on the history of HNA, which went under a mountain of debt and was unwound by the Chinese government.
HNA started off as Hainan Airlines before expanding internationally and across sectors.
Wokeness as mainline orthodoxy – Noahpinion – Musa al-Gharbi has a recent article with quite a bit of data showing that journalistic and academic attention to the topics of diversity, bias, privilege, and so on seems to have peaked, while “cancel culture” incidents have decreased on campuses and in corporations, and political opinions on various social issues have moderated a bit. Anecdotally, corporate interest in DEI seems to be waning as well. Other observers like Tyler Cowen have noticed the trend.
Luxury
Survey Finds Japanese People’s Dream Car Is a Lexus | Nippon.com – bad news for Mercedes & BMW. This isn’t about Japanese nationalism as Mercedes and BMW have enjoyed healthy sales in the country in the past. Much of this is about the massification of these brands and the decline in quality in comparison to the single-mindedness of Lexus engineers.
Marketing
The Drum | How Nestlé Is Using AI To Set Creative Rules For Its 15,000 Marketers – In 2021, Nestlé started to put all its creative through an AI platform that would rank ads based on their suitability to different online platforms and pull out the key elements that are required for maximum ROI. That process created a set of ’rules’ for successful campaigns and early tests generated transformational results, finding that ads that meet the new creative requirements generate a significantly higher return on ad spend. Now, Nestlé’s 15,000 marketers across 2,000 brands in 200 territories have to test the ads in the machine learning platform prior to rolling a campaign out – my biggest concern is that this becomes reductive in terms of creativity and self reinforcing rather than facilitating the picking of true winners. Secondly, I could see it over-indexing on brand activation rather than brand building spend and ultimately destroy value
Hong Kong Stock Market filing – the Company (China Renaissance Holdings – *added this for clarity) has been unable to contact Mr. Bao Fan (“Mr. Bao”), Chairman of the Board, Executive Director, Chief Executive Officer and the controlling shareholder of the Company. The Board is not aware of any information that indicates that Mr. Bao’s unavailability is or might be related to the business and/or operations of the Group which is continuing normally (PDF) – Bao Fan has been incommunicado for a number of days. He is not responding to messages. While its unusual and considered bad practice having the same person as chairman and CEO, in China its more common. So Bao’s dual role at China Renaissance Holdings isn’t unusual. But that is the least of the worries that western investors will have about China Renaissance Holdings at the moment.
Meituan delivery workers waiting for the food to be prepared
Some thoughts:
China Renaissance Holdings has been involved in funding some of China’s biggest technology companies including Didi (think of Lyft or Uber as a western analogue) and Meituan (Deliveroo, Doordash or Just Eat equivalent.
Didi in particular seems to have gained the wraith of the Chinese government. Some of this feels to be down to sexism due to the company having a connected female president Jean Liu. The party leans more toward the Andrew Tait school of feminism
Mr Bao Fan’s disappearance evoked memories of Jianhua Xiao and his company Tomorrow Holdings. Xiao was snatched and smuggled out of his apartment in the Four Seasons in Hong Kong back in 2017. Xiao for a few years all that people knew was that he was wheeled out of the hotel asleep in a wheelchair despite having a security team. He then spent a few years ‘helping‘ authorities unwind his business Tomorrow Holdings. Finally, he got sent to prison for 13 years with charges including embezzlement and fraud. If this happens with China Renaissance Holdings, or any of the prominent companies that it has as clients like Meituan there would be a shockwave, even through the most pro-China of foreign investors like Bridgewater Capital or Goldman Sachs
Bao Fan is one of several executives who were disappeared for a while. The most prominent executive who disappeared from the public eye was Jack Ma. Ma then stepped back from his businesses. If Bao steps back from China Renaissance Holdings, the Chinese tech sector will lose an investment rainmaker. China Renaissance Holdings maybe unwound or its assets handed over to state-owned banking institutions
What happens next will likely impact western sentiment towards Chinese investment in the short to medium turn, but financial institutions are still seduced by the ‘Chinese opportunity’. And the smart money this time might be wrong
Last week I heard the acronym NORA mentioned with regards the kind of problems that Microsoft’s algorithm could solve. NORA stands for no one real answer. Search is already pretty good at answering questions like ‘what time is it in Osaka’ or ‘what is the capital of Kazakhstan’.
In the mid-2000s NORA would have been called ‘knowledge search‘ by the people at Google, Yahoo! and Bing – who were the main search engine companies. So its not a new idea in search, despite what one might believe based on the hype around chatbot enabled search engines. ChatGPT and other related generative AI tools have been touted as possible routes to get to knowledge search.
Knowledge search
Back when I worked at Yahoo! the idea of knowledge search internally was about trying to carve out a space that useful and differentiated from Google’s approach as defined by their mission:
To organise the world’s information and make it universally accessible and useful
Google was rolling out services that not only searched the web. It also covered maps, the content of books including rare libraries and academic journals. It was organising the key news stories and curating which publications were seen in relation to that story. It could tell you the time elsewhere in the world and convert measures from imperial to metric.
Google’s Gmail set the standard in organising our personal information, making the email box more accessible and searchable than it had been previously. We take having a journaled hard drive for granted now, but at one time Google Desktop put a search of the files on your computer together with online services in one small search box.
Being as good as Google was just table stakes. So when I was at Yahoo! we had our own version of Google Desktop. We bought Konfabulator, that put real time data widgets on your desktop and were thinking about how to do them on the smartphone OS of the time Nokia’s Symbian S60. Konfabulator’s developer Arlo Rose went on to work on Yahoo!’s mobile experiences and Yahoo! Connected TV – a photo-smart TV system that was before the modern Apple TV apps. Tim Mayer led a project to build out an index of the web for Yahoo! as large, if not bigger than Google’s at the time. And all of these developments were just hygiene factors.
My colleagues at Yahoo! were interested in opinions or NORA; which is where the idea of knowledge search came in. Knowledge search had a number of different angles to it:
Tagged content such as my Flickr photo library or social bookmarking provided content from consumers about a given site that could then be triangulated into trusted context, or used to train a machine learning model of what a cat looked like
Question and answer services like Quora, Yahoo! Answers and Naver’s Jisik In Service improved search. Naver managed to parlay this into becoming the number one search engine for Korea and Koreans. Google tried to replicate this success with Knol and failed
Reviews. Google managed to parlay reviews into improving its mobile search offering. Google acquired Zagat in 2011. This enabled Google to build a reputation for good quality local restaurant reviews. It eventually sold the business on again to another restaurant review site The Infatuation
The ChatGPT type services in search are considered to provide an alternative to human-powered services. They create NORA through machine generated content based on large data sets trawled from the web.
Energy consumption
A conventional Google internet search was claimed to consume 0.3 watt/hours of power according to Google sources who responded to the New York Times back in 2011. This was back when Google claimed that it was processing about one billion (1,000,000,000) searches per day. It accounted for just over 12 million of the 260,000,000 watt hours Google’s global data centres use per day. The rest of it comes from app downloads, maps, YouTube videos.
But we also know that the number of Google searches ramped up considerably from those 2011 publicly disclosed numbers
The driver for this increase was mobile search including more energy intensive Google Lens and voice activated searches thanks to Android.
Large language models (LLMs) are computationally intensive and this will result in a corresponding rise in energy consumption. That also has implications in terms of business profit margins as well as ESG related considerations.
Legal liabilities
With NORA content being created by machine learning services, it might be different to the previous generation of knowledge search services. These services were platforms, but machine learning services become publishers.
This becomes important for a few reasons
Increased costs (while they aren’t using an army of writers, they are using a lot of computing power to generate the responses)
Legal protections (in the US)
Intellectual property and plagiarism issues, currently they can handle it just by taking down the content. Once they become a publisher rather than a platform things become more complicated
“no provider or user of an interactive computer service shall be treated as the publisher or speaker of any information provided by another information content provider”
Communications Decency Act of 1996.Section 230
Section 230 has been repeatedly used to regulate Facebook, Google et al in a lax manner as they haven’t been ‘publishers’, with ChatGPT this may change. The question of whether an algorithm is a creator has some precedence. Financial reporting has used machine learning to create news reports on company financial results over a number of years. Combine that with the general political antipathy towards Meta and Alphabet from both of the main US political parties and things could get interesting very fast.
It is interesting that OpenAI is putting a lot of thought around ethics in LLM, which will impact future services and they probably hope stave off regulation.
Regulated industries and liability
Given an LLM’s ability to make things up it can:
Gives advice without pointing out health risks by creating a workout plan or a weight loss diets
Gives bad legal advice
Infringe regulations surrounding different industries like financial services
This is just the tip of the iceberg that NORA content powered by LLMs face.
Business model disruption
Search advertising as we know it has been the same for the past two decades. The disruption to the look and feel of search results through Bing’s chat response has a negative impact on Google’s advertising model with the search ads along the top and down the right hand side of the search engine results page. Instead you’ll end up with the ‘correct’ answer and no reason to click on the search adverts.
Currently if a non-relevant site shows up in Google. The lack of relevance is blamed on the site rather than the search engine. However an error in a machine learning created NORA response will see the search engine blamed.
Which is pretty much what happened when Google demonstrated their efforts in the area. Inaccuracies in a demonstration held in Paris cause the share price of Alphabet to decline by 7 percent in one day. Technology news site TechCrunch even went as far as to say that Google is losing control.
Microsoft probably doesn’t have a lot to lose in Bing. So integrating ChatGPT’s LLM might give them a few percentage points of search market share. Microsoft thinks that each percent gain would be worth 2 billion dollars in extra revenue.
The 2 billion number is an estimate and we don’t know how the use of NORA results generated by LLM will affect bidding on search keywords. That 2 billion might be a lot less.
Is NORA the user problem that Google and Bing’s use of LLMs are fixing?
Around about the time that Google enjoyed a massive uptake in search it also changed search to meet a mobile paradigm. Research type searches done by everyone from brand planners to recruiters and students have declined in quality to an extent that some have openly questioned is Google dead?
Boolean search no longer works, Danny Sullivan at Google admitted as much here. While Google hasn’t trumpeted the decline of Boolean search, ‘power’ users have noticed and they aren’t happy. That narrative together with the botched demo the other week reinforced each other.
Unfortunately, due to the large number of searches that don’t require Boolean strings, Google wasn’t going to go back. Instead, chat-based interfaces done right might offer an alternative for more tailored searches that would be accessible to power users and n00bs alike?
Technology paradigm shift?
At first the biggest shock that myself and others had seeing the initial reports was how Google and Microsoft could have been left in the dust of OpenAI. Building models requires a large amount of computing power to help train and run.
Microsoft had already been doing interesting things in machine learning with Cortana on Azure cloud services and Google had been doing things with TensorFlow. Amazon Web Services provides a set of machine learning tools and the infrastructure to run it on.
Alphabet subsidiary DeepMind had already explored LLM and highlighted 21 risks associated with the technology, which is probably why Google hadn’t been looking for a ChatGPT type front end to search. The risks highlighted included areas such as:
Discrimination, Hate speech and Exclusion although there is research to indicate that there might be solutions to this problem
Information Hazards – there has already been a case study on how an LLM can be influenced to display a socially conservative perspective.
Misinformation Harms – researchers claimed that LLMs were “prone to hallucinating” (liable to just make stuff up)
Malicious Uses
Human-Computer Interaction Harms
Environmental and Socioeconomic harms
Stories that have appeared about ChatGPT and Bing’s implementation of it seem to validate the DeepMind discussion paper on LLMs.
The Microsoft question of why they partnered with ChatGPT rather than rolling out their own product is more interesting. Stephen Wolframs in-depth explanation of how ChatGPT works is worth a read (and a couple of re-reads to actually understand it). Microsoft’s efforts in probabilistic machine learning looks very similar in nature to ChatGPT. As far back as 1996, then CEO Bill Gates was publicly talking about how Microsoft’s expertise in Bayesian networks as a competitive advantage against rivals. Microsoft relied on research and the Bayesian network model put forward by Judea Pearl which he describes in his book Heuristics.
Given the resources and head start that Microsoft had, why were they not further along and instead faced being disrupted by OpenAI? Having worked in the past with Microsoft as a client, I know they won’t buy into anything that they can build cheaper. That raises bigger questions about Microsoft’s operation over the past quarter of a century and its wider innovation story to date.
Flash in the pan
At times the technology sector looks more like a fashion industry driven by fads more than anything else. A case in point being last years focus on the metaverse. The resulting hike in interest rates has seen investment drop in the field. Businesses like Microsoft and Meta have shut down a lot of their efforts, or have scaled back. It is analogous to the numerous ‘AI winters‘ that have happened over the past 50 years as well.
Bing’s implementation of LLM is already garnering criticism from the likes of the New York Times. This new form of search may end up being a flash-in-the-pan like Clubhouse. The latent demand for NORA in search will still be there, but LLM might not be the panacea to solve it. Consumers may continue to rely on Reddit and question-and-answer platforms like Quora as an imperfect solution in the meantime.
In summary….
NORA content generated by LLMs represent a new way to solve a long known about challenge in online search
NORA as a concept was previously called knowledge search
NORA content competes with: social media including Reddit, specialist review sites including Yelp or OpenRice and question and answer services including Quora
ChatGPT and similar services affect human perceptions of search and the experience makes them more critical of the search engine response is not of an acceptable standard
LLMs represent a number of challenges that large technology companies have discussed publicly, but were still attractive for some reason
ChatGPT shows up the the decades of research that Google, Microsoft and Amazon have put into machine learning, this will negatively affect investors attitudes to these companies and merits a more critical nuanced examination of ‘innovation’. These large companies seem to be struggling to put applied innovation into practice. Microsoft buying into ChatGPT is essentially an admission of failure in its own efforts over at least 3 decades. Even ChatGPT’s deeply flawed product is considered to be better than nothing at all by these large technology companies
Use of ChatGPT like services expose Google and Bing to business risks that are legal and regulatory in nature. It could even result in loss of life
ChatGPT’s rise has surfaced deep seated concerns amongst technologists, early adopters, power users and investors about Google’s ability to execute on innovation successfully now (and in the future). Google’s search product has been weakened over time by its focus on mobile search dominance. Alphabet as a whole is no longer seen as a ‘leader’
LLMs, if successful would disrupt the online advertising business model around search engine marketing
ChatGPT and its underlying technology do not represent a paradigm shift
There is evidence to suggest that ChatGPT and other LLM powered chat search interfaces could turn out to be a fad rather than a future trend. The service as implemented has underwhelmed
