Two Types: Bias‑aware Users and Self‑proclaimed Polymaths
There are two categories of people: those who quickly figure out that chatbots give you the answer you expect when you ask questions in a biased way, and the ascended polymaths currently out-thinking every expert on Earth
Impossible Returns Signal Superhuman AGI's Arrival
One of the first signs of the emergence of superhuman AGI will be the emergence of a quantitative trading firm with impossible returns
Short-Term References Matter; Long-Term Lose Relevance
Short term, this is still the best reference point. Long term, past references might become much less useful.
Frontier Models Overfit ARC Format, Limiting Generalization
Interesting finding on frontier model performance on ARC -- due to extensive direct targeting of the benchmark, models are overfitting to the original ARC encoding format. Frontier model performance remains largely tied to a familiar input distribution.
AI Diagram Tool Still Slower than Manual Slides
Right now it's still taking me more time to generate medium-complexity diagrams by describing them to Nano Banana than by drawing them manually in Google Slides...
AGI Growth Limited by Fundamental Bottlenecks, Not Scaling
I don't think the rise of AGI will lead to a sudden exponential explosion in AI capabilities. There are bottlenecks on the sources of new capability improvements, and horizontally scaling intelligence in silicon (even by a massive factor) doesn't lift...
AGI Arrives When No Test Shows Human‑AI Gap
Reaching AGI won't be beating a benchmark. It will be the end of the human-AI gap. Benchmarks are simply a way to estimate the current gap, which is why we need to continually release new benchmarks (focused on the remaining...
Call Centers Signal AI‑Driven Job Crisis Ahead
A good canary in the coal mine for AI-caused job loss will be call centers. We're currently projecting ~2.75M call center jobs in the US in 2026. In 2016 it was ~2.63M. The global call center market size has grown...
ARC Advances Driven by Test-Time Adaptation, Not LLM Scaling
Lots of folks spread false narratives about how ARC-1 was created in response to LLMs, or how ARC-2 was only created because ARC-1 was saturated. Setting the record straight: 1. ARC-1 was designed 2017-2019 and released in 2019 (pre LLMs). 2. The...
Gemini Deep Think Sets Record on ARC‑AGI‑2
The new Gemini Deep Think is achieving some truly incredible numbers on ARC-AGI-2. We certified these scores in the past few days. https://t.co/Q9qeJbCObK
Write High‑performance TPU/GPU Kernels in Python
You no longer need to leave Python to write high-performance hardware kernels. Learn how to use Pallas in Keras to author custom ops that lower to Mosaic for TPUs or Triton for GPUs: https://t.co/oeV4cmV4M0
AI Offloads Cognitive Load, Defying Age‑Related Brain Decline
One positive outcome of AI is that it will make the aging-related decline of your brain power less relevant. You can keep doing the same things just as nimbly at any age by offloading more.
More Code, More Liability: Speed Isn't Always Blessing
I tend to view code as more of a liability than an asset. In this light, making it cheaper and faster to generate a lot of code might not be an unmitigated blessing.
GenAI Raises Baseline, Makes Mediocrity Economically Irrelevant
GenAI will not replace human ingenuity. It will simply raise the floor for mediocrity so high that being "pretty good" becomes economically worthless.
Overused Vagueposting Fuels AI Lab Fatigue
Grandiose vagueposting on Twitter is the one tried and true marketing strategy for AI labs. But as it gets overused it eventually creates fatigue
Transformers Need Internal Scratchpad for Sequential Reasoning
The Transformer architecture is fundamentally a parallel processor of context, but reasoning is a sequential, iterative process. To solve complex problems, a model needs a "scratchpad" not just in its output CoT, but in its internal state. A differentiable way to...
AI Should Augment, Not Replace, Human Thought
The goal of AI should not be to replace human thought and human agency, but to expand them. Not everything needs to be automated.
From Library to Scientist: AI’s Next Evolution
LLMs represent the "library" phase of AI. The next phase will be the "scientist" phase. A library contains answers, but a scientist knows how to find answers that don't exist yet.
LLMs Aid Brainstorming, but AI Needs Fresh Ideas
Evaluating the potential of LLMs to help with scientific discovery. In short: new ideas are direly needed to move AI towards invention. LLMs can be useful as brainstorming partners though. https://t.co/Zd0EKf8Z3n
Keras 3.13 Introduces LiteRT Export and GPTQ Quantization
New Keras release: 3.13 🎉 Some major new features: • Model export to LiteRT (formerly TFLite) for mobile/edge • GPTQ quantization support for post-training compression • New Adaptive Pooling layers for dynamic architectures https://t.co/Ogmag7FYCY
Innovation Thrives on Strong Links, Not Weakest Links
Innovation is a "strong-link problem". In a chain (weak-link problem), the weakest element breaks the system. In discovery (strong-link problem), the strongest element makes the breakthrough. The rest of the system provides the infrastructure that allows the outlier to function
Our Brains Are Tuned to the Universe’s Stable Laws
Because our universe follows stable laws, a sufficiently general intelligent system adapted to it, like human-driven science, can eventually model any phenomenon within it. Human intelligence may not be "universal" in the mathematical sense (see No Free Lunch theorem), but we...
Collective General Intelligence Enables Science to Solve Any Solvable Problem
I would say there is no such thing as "universal" intelligence but there is definitely such a thing as "general" intelligence, and as a collective, we have it. "Science", modeled as an intelligent system (primarily powered by human intelligence) can solve...
Benchmark Humans Against the Best Alternative, Not Averages
You should measure human capability on a task not in terms of "average human" or "random human", but in terms of your best alternative (to AI) if you were to hire a human to solve the task. Which isn't average...
Anticipating the Upcoming ARC‑AGI‑3 Performance Numbers
Looking forward to the ARC-AGI-3 numbers :)
AI Shifts From Automation to Invention via Symbolic Search
AI will evolve from being an automation machine to becoming an invention machine. This will require a fundamentally new paradigm, with symbolic search as its core, not curve-fitting
Intelligence Requires Exploration, Goal‑Setting, and Planning
Fluid intelligence as measured by ARC 1 & 2 is your ability to turn information into a model that will generalize. That's not the only thing you need to make an intelligent agent. To start with, when you're an agent in...
Test‑time Adaptation Unlocks Fluid Intelligence, but AGI Still Distant
Back in 2019, ARC 1 had one goal: to focus the attention of AI researchers towards the biggest bottleneck on the way to generality, the ability to adapt to novelty on the fly, which was entirely missing from the legacy...
Edit LLM Behavior Safely without Retraining, Says CTGT
Cyril and the team at CTGT are productizing mechanistic interpretability. They make it possible to edit the behavior of LLMs to add safety policy guarantees without retraining, in a way that is much more reliable than simple prompting.
ARC 2025 Highlights LLM Refinement & Zero‑Pretraining Advances
Congrats to the ARC Prize 2025 winners! The Grand Prize remains unclaimed, but nevertheless 2025 saw remarkable progress on LLM-driven refinement loops, both with "local" models and with commercial frontier models. We also saw the rise of zero-pretraining DL approaches like HRM...
Join Keras Community Meeting Today for Roadmap Updates
The Keras community video meeting is happening today at 10am PT (in 1 hr 10 min). Join to get updates on the development roadmap and ask questions to the Keras team. URL in next tweet
True AGI Demands General Learning, Not Task Stacking
Either you crack general intelligence -- the ability to efficiently acquire arbitrary skills on your own -- or you don't have AGI. A big pile of task-specific skills memorized from handcrafted/generated environments isn't AGI, not matter how big.
Waymo on Track to Cover over Half US by 2028
My prediction of Waymo covering >50% of the US by eoy 2028 is looking good
AI Will Cross a Self‑improvement Threshold, Leading to Gradual Progress
There's a specific threshold of complexity and self-direction below which a system degenerates, and above which it can open-endedly self-improve. Current AI systems aren't close to it yet. But it's inevitable we will reach this point eventually. When we do, we...
Waymo Goes Fully Driverless in Dallas After Rapid Growth
Waymo started testing with a safety driver in Dallas just 4 months ago. They're now fully driverless -- no one but you in the car. Waymo has been expanding at >500% per year.
True Understanding Equals Minimal Compression, Not Massive Parameter Counts
To perfectly understand a phenomenon is to perfectly compress it, to have a model of it that cannot be made any simpler. If a DL model requires millions parameters to model something that can be described by a differential equation of...
Half‑Price Deep Learning with Python 3rd Edition Today
Black Friday deal for Deep Learning with Python (3rd edition): 50% off, just today. Go buy it: https://t.co/EL58J1Zl22
I’m Unable to View the Linked Content, so I Can’t Create a Headline.
https://t.co/XJNnjRCyYL
Gemini 3 Hits 31.1% on ARC‑AGI‑2 Benchmark
Gemini 3 scores 31.1% on ARC-AGI-2. Impressive progress.
Waymo Expands to Five New Cities, Scaling Fivefold Annually
Waymo is adding 5 new cities: Miami, Dallas, Houston, Orlando. Waymo has been growing about 5x per year since it started scaling its service in 2023.
Infinite AGI Returns Myth Inflates Tech Investment Tenfold
The notion that AGI would have infinite returns has been used to justify investment far above expected returns (by 10x-100x) for technology that is neither AGI nor on the path to AGI
Algorithms Now Outpace Labs as Science’s Primary Tool
The most powerful scientific instrument of the 21st century isn't the electron microscope or the particle collider. It's the algorithm. Today, a scientist in biology, physics, chemistry etc. is more likely to be debugging a Python script than to be running...
TSGM: Keras 3 Library for Synthetic Time‑Series Generation
TSGM is a Keras 3 based library for generating synthetic timeseries datasets: https://t.co/cKNN2PJtG7
Deep Learning Demystified: Intuition‑Driven Modern Stack Guide
Deep learning is not a collection of black-box tricks, contrary to what many believe. It can be learned as a principled engineering discipline. This latest edition of Deep Learning with Python is my best attempt so far at teaching it. It...
Boost Colab Training Speed 4‑5× with TPU and Steps_per_execution
If you're using Colab and you feel like training your model on GPU is slow, switch to the TPU runtime and tune the "steps_per_execution" parameter in model.compile() (higher = more work being done on device before moving back to host...
ML Research: Build, Test, Learn—Not Just Speculate
ML research is an engineering discipline, not a philosophy seminar. You build, you test, you learn. Untested ideas are just speculation.
Autonomous AI Evolves by Coding Its Own Models
The path to autonomous AI is a system that learns to solve new problems by synthesizing models of them on the fly (as code), and that gets smarter over time by adding new abstractions to its own library (also as...
Understanding = Ability to Act Appropriately in Any Situation
For me, what it means to "understand" something can be characterized purely behaviorally. You understand a thing if you have the ability to act appropriately in response to situations related to the thing. You understand how to make coffee if you...
AGI's Solution Will Seem Obvious in Hindsight
When you see the solution to AGI you will find that it was in fact so straightforward as to be obvious, and that it could have been developed decades ago
One Day Left: Leaderboard Shifts, Overfitting Warning
One day left to submit to ARC Prize 2025 on Kaggle! Big changes at the top of the leaderboard these past few days, with the rise of teams NVARC and North Stars. Close contest between GiottoAI and ARChitects for the top...