Depends on how you spin it I guess (screenshots from 2 different articles). People working at universities are pushed so incredibly hard to ensure that every study is a breakthrough that they just...lie. All the time. Probably without even realizing it. www.standard.co.uk/news/tech/im...

Every Jan 1 I post a scorecard on predictions I made, with dates, on Jan 1, 2018 on cars (self-driving), robots, AI, & ML, and on human spaceflight. Besides telling which turned out right and which wrong in the last year I also talk a lot of smack about these topics. rodneybrooks.com/predictions-...

LLMs can be also seen as big bags of heuristics: arxiv.org/abs/2410.21272

𝗢𝟯 𝘄𝗮𝘀 𝘁𝗿𝗮𝗶𝗻𝗲𝗱 𝗼𝗻 𝟳𝟱% 𝗼𝗳 𝘁𝗵𝗲 𝗽𝘂𝗯𝗹𝗶𝗰 𝘀𝗲𝘁 𝗳𝗼𝗿 𝗔𝗥𝗖-𝗔𝗚𝗜. OpenAI did not disclose this in the video. Sam said they didn’t target the test. Never trust a staged demo. Never trust a product you haven’t tried. Never trust OpenAI.

o3, AGI, and the art of the demo. Long read on what OpenAI didn’t tell you yesterday. garymarcus.substack.com/p/o3-agi-the...

Likewise, a simple adversarial strategy beats "superhuman" Go-playing algorithms: goattack.far.ai It's wise to remember that there is no scientific consensus on what "intelligence", actually is.

Just for those who don't know: the vast majority of open problems in maths, are not numerical in nature.

The questions have numerical answers, so it is easy to check whether it gets them right.

How many times do we have to see this same movie, where an AI beats some benchmark and influencers gleefully shout “It’s So Over” without even trying out the AI and then on careful inspection the AI turns out to not be robust or reliable? Thousands? (It’s already been hundreds.)

It seems that OpenAI's latest model, o3, can solve 25% of problems on a database called FrontierMath, created by EpochAI, where previous LLMs could only solve 2%. On Twitter I am quoted as saying, "Getting even one question right would be well beyond what we can do now, let alone saturating them."

It's widely agreed that scholars are supposed to say when they use ChatGPT. Yet phrases like "I am an AI language model"—with no disclosure—are popping up in papers. I wrote about how journals seemingly aren't enforcing their AI policies, according to a new study: www.chronicle.com/article/scho...

This seems like a pretty balanced commentary. They certainly get this right: "connection between capability improvements & AI’s social or economic impacts is extremely weak. The bottlenecks for impact are the pace of product development and the rate of adoption" www.aisnakeoil.com/p/is-ai-prog...

Good reporting here, but sadly, these tragedies were predictable. Those of us who actually work on machine learning know that deep-learning based computer vision simply isn't reliable enough for safety-critical applications such as self-driving cars. @garymarcus.bsky.social @filippie509.bsky.social

The late Suchir Balaji’s blog post on AI, copyright and fair use, reposted in his memory. suchir.net/fair_use.html

The bootstrap can be used to generate a new random sample from an existing random sample. Its validity can be guaranteed by the Glivenko-Cantelli theorem, which demonstrates how the empirical cumulative distribution (CDF, top panel), converges on the CDF of the sample (bottom panel).

For an increasing function 𝑓:ℝ→ℝ, max(𝑓(𝑎),𝑓(𝑏))=𝑓(max(𝑎,𝑏)). An important special case is 𝑓(𝑥)=𝑥+𝑐, for which we obtain max(𝑎+𝑐,𝑏+𝑐)=𝑐+max(𝑎,𝑏).

Since 2016 Waymo raised ~$25B, so they burn ~$3B/y or little over 8mln/day. With ~700 cars, assuming they operate each car every day, it costs them over 11k dollars to operate each of their cars per day. $11k PER DAY per CAR. If you don't find this ridiculous IDK what else to say.

Suchir Balaji was a good young man. I spoke to him six weeks ago. He had left OpenAI and wanted to make the world a better place. This is tragic.

Very proud of the Birmingham HDRUK PhDs!

Health Data Research UK PhD meet! Work from Ant Lee and Jianqiao Mao (latter with @maxal.bsky.social)

Apple "Intelligence". @garymarcus.bsky.social

As first predicted some 10 years ago that is how "self driving cars" will end - as glorified driver assistance features. The graveyard of autonomous vehicle efforts is pretty crowded already with pretty much only Waymo remaining, until life support from Google mothership ends.

What if all the hype just didn’t turn out to be true? Evidence of productivity gains is mixed - yet hypey takes continue to dominate in the media.

Don’t Ride This Bike! Generative AI’s persistent trouble with compositionality and parts, by Gary Marcus @garymarcus.bsky.social and Ernest Davis / Marcus on AI - Substack garymarcus.substack.com/p/dont-ride-...

Not quite: AI got people excited about interpolation, it seems. Numerical analysts suddenly feel seen.

Fully-funded PhD position available. If you are interested in machine learning for signal processing of biosignals, please do get in touch.

New blogpost: deevybee.blogspot.com/2024/11/why-...

The current incarnation of AI companies earnestly engaged in the Sisyphean task of labeling "all the things, in every circumstance".

Read this article.

Nice, terse quote: "There is no principled solution to hallucinations in systems that traffic only in the statistics of language without explicit representation of facts and explicit tools to reason over those facts."

Game over, I won. GPT is hitting a period of dimishing returns, just like I said it would. Analysis and breaking news here: open.substack.com/pub/garymarc...

Can we be confident that rigour-enhancing practices causally increase the replicability rate of scientific studies in social science? A high-profile claim of that specific cause-effect relationship was found to have insufficient rigour, now retracted. statmodeling.stat.columbia.edu/2024/09/24/w...

In other science reform implosion news, the contested article including OSF & Data Colada authors on how preregistration & other rigor-enhanching practices led to high observed replicability (the one that couldn't produce its own preregistration) was just retracted www.nature.com/articles/s41...

this is pretty amazing: @lucinauddin.bsky.social is taking on the giant, hugely profitable publishers of academic journals, on grounds of antitrust If you'd like to join the case as a plaintiff you can sign up at www.lieffcabraser.com/antitrust/ac... summary of the case:

In case you don’t believe the same equations describe motion in the atmosphere and the ocean.

"By creating the illusion of complete autonomy, companies can fuel interest in their technology and raise the billions of dollars they need to build a viable robot taxi service." Waymo & Cruise recently admitted they use remote assist. Zoox is more up front about it. www.nytimes.com/2024/09/11/i...

1/ Here's a critical problem that the #neuroai field is going to have to contend with: Increasingly, it looks like neural networks converge on the same representational structures - regardless of their specific losses and architectures - as long as they're big and trained on real world data. 🧠📈 🧪

“AI worse than humans in every way at summarizing information … the technology might actually make more work for people, not less”