4 January 2026
News
End-of-year M&A
There was a final flurry of AI M&A at the end of the year. Alphabet will pay $4.75bn for Intersects Inc., which provides data centre electricity systems, helping Google get power to new DCs quicker. Meta bought Manu, which makes enterprise research agents that got a lot of attention a few months ago: the price was undisclosed but apparently ‘more than $2bn’. And most dramatically, Nvidia did an acquihire of Groq, paying $20bn for a non-exclusive licence, with the key staff moving to join Nvidia and the investors getting a payout. Groq was founded by members of Google’s TPU AI accelerator chip team nine years ago, and raised at only $7bn in October. ALPHABET, MANUS, NVIDIA
In non-tech news, Larry Ellison, who founded Oracle (ask your parents), made a personal guarantee of $40bn towards his son’s bid to buy Warner Bros. Netflix remains the company’s preferred buyer, though. LINK
The week in AI
The ACCA, which is the largest chartered accounting body, is ending remote exams because AI makes it too easy to cheat. LINK
Google is suing SerpAPI, a company that scrapes its search results and sells the data to third parties, most obviously to Perplexity and other AI companies that want to do their own search results without having their own search engine. LINK
OpenAI published an engineering post on how it tries to limit prompt injection in its Atlas web browser (remember that?). ‘Prompt injection’ here means that there could be text hidden in any web page you visit that the ChatGPT agent embedded in the browser would interpret as instructions - to email your bank details somewhere, for example. It’s not at all clear whether this is a solvable problem. LINK
New cars
Waymo will extend its autonomous taxi service to London in 2026. Meanwhile, Uber and Lyft are partnering with Baidu to trial its AV service in London as well. Back in the USA, Tesla’s robotaxi project in Austin is now experimenting with removing the human safety drivers (Tesla is currently running 30-40 cars there, with humans sitting in the car ready to take over for the ‘full self-driving’). LONDON, TESLA
Meanwhile, Tesla sales continue to slide and BYD is now outselling it on pure battery-driven cars. Some of this Tesla sales slump is about Elon Musk’s behaviour (especially in Europe, and in the US demographics that most like EVs), but it’s hard to see that being as visible in China, and meanwhile the product line-up is stale too. It seems pretty clear that Elon Musk wants to pivot away from EVs, where there’s little new to say and competition will be ferocious, and upwards to both autonomy (sigh) and now robots. LINK
Ideas
The Information has more gossip about OpenAI’s plans for advertising. I’m old enough that this reminds me of MySpace after Rupert took over. LINK
Huawei now makes the best-selling car in China in the over-$100k segment, the Maestro S800, outselling any foreign car in that range. Meanwhile, BYD is making a car with a frame cast in a single piece. HUAWEI, BYD
The FT has a long interview with Yann LeCun talking about his new venture, and AI at Meta - the old team was indeed ‘selective’ in its use of benchmarks for the flopped Llama 4, which lost Mark Zuckerberg’s confidence, and most of that team has either left or (he thinks ) will leave. The new team, headed by billion-dollar hire Alex Wang, is good, but as he keeps saying, he thinks LLMs are a dead-end and more progress needs real-world data (cause-and-effect, video). LINK
Coupang, the ‘Amazon of South Korea’, has had a breach, in which a former employee stole user data for 34m customers. The company post-mortem is wild, including a MacBook thrown into a river. LINK
Outside interests
Relevant to AI, but interesting in its own right: how far can animals be tricked by conjuring tricks? Here, the Jay. LINK
The NY Times process holding the front page. LINK
Mark Curtis, co-founder of Fjord, on the journey of design from ‘interactive media’ in the early 90s to generative AI today. LINK
Data
Analysing how developers used AI coding in 2025. LINK
Column
Big tech’s 2026
There’s an obvious set of questions for AI in 2026, at each level of the stack - does the rate of model improvement change, do we have some new breakthrough (continuous learning?) or change in cost, does Nvidia get more competition, and what happens to the data centre boom / bubble? Here, though, I’m considering the strategies of the big tech companies themselves, as three years into the AI cycle they pivot themselves around this.
Google had an innovator’s dilemma question (can they do this if it threatens the legacy business?) and a Steve Ballmer question (can Sundar Pichai do this?) and now seems to have passed both of those. The models have caught up and the product teams are doing pretty well both in making this a feature (AI Answers, and a lot of other things) and trying to find new experimental products. Meanwhile, the fortress balance sheet and the decade of investment in TPUs are a good setup for a few hundred billion dollars of data centre deployment. They do, however, have to get the API and pricing story right for GCP. But on the other hand, we still don’t know if someone (else) will work out the real ‘step two’ for how LLMs can change search, and make another attempt to unbundle Google.
Apple has time. Siri will probably get fixed, and be a lot better, or at least good enough, but that won’t really matter. The hardware is still the best, and the base case is that iPhones will remain the best way to use whatever LLM experiences end up finding product-market fit, just as the iPhone is the device to use other third-party services like YouTube or Uber. Jony Ive is working on… something, probably audio, and OpenAI would certainly like to become an app platform, but it’s not at all obvious why that would make you replace the slab of glass in your pocket with something else. Meanwhile, glasses, which could change everything, are still on the horizon, and the (involuntary) replacement of the head of UX will hopefully improve the software, which has tended towards mediocrity of late. Otherwise… treading water.
Meta, like Google, is working hard to rebuild its recommendation and ad systems around generative AI, and it would really like to have its own SOTA models to do that. But this might also be the year we get something like Sora, but good - a real take-off of generative content that maps directly against Instagram (and YouTube, and TikTok). Do users care if that image is ‘real’? It depends - this is a little like asking if you care whether the singer wrote the song. Authenticity is contextual. But the central story of Facebook since it was founded is surfing user behaviour, so if user behaviour shifts around this, Facebook will follow.
Amazon seems to have a lot of different questions. What happens to that $65bn ad business - does AI unlock more advertisers and better targeting, or do purchasing agents bypass the ads? Will there be a step-change in the quality and character of recommendations - can Amazon finally scale a real understanding of what the products are? Can it do merchandising instead of showing you more SKUs? Meanwhile AWS, of course, has the same boring margin, price, and API execution questions as GCP.
Microsoft is weird. It did the OpenAI deal, enterprise money is flooding in, and most enterprises expect Microsoft to capture a large chunk of their AI migration spending. But it still has no top-tier models of its own, and ‘Copilot’ has become a resented surcharge for a random set of features many people don’t use - indeed, ‘Copilot’ is the new ‘Watson’. Satya Nadella did a superb job of changing the narrative, but where are the compelling and innovative new products?
And then, finally, there’s OpenAI, which I suppose counts as big tech now. It has all the mindshare and brand recognition, 800m weekly users, and everyone is throwing money at it. But there is no sustainable tech lead, no network effect, no real product advantage, and no real product-market fit. Those 800m users have pretty limited engagement, and they can all leave - the base is a mile wide but an inch thick. And meanwhile, Google and Meta are leveraging their distribution to make this a feature. So, Sam Altman is frantically swapping overpriced paper for hard assets and market position before the music stops.