961
Notion AI: Unpatched data exfiltration
Notion AI was susceptible to data exfiltration via indirect prompt injection due to a vulnerability in which AI document edits are saved before user approval.
962
TorchTPU: Running PyTorch Natively on TPUs at Google Scale
Discover TorchTPU, Google’s new engineering stack designed to run PyTorch natively on TPU infrastructure with peak efficiency. Learn how its "Eager First" philosophy and XLA integration simplify model migration while unlocking massive scalability for the next generation of AI.
963
How we index images for RAG
Reading the screenshots, diagrams and tables in technical documentation for LLMs
964
The Companies Cutting Headcount for AI Will Lose to the Ones Who Didn't
Organisations using AI to cut headcount are making a short-term trade with long-term consequences. The ones holding their teams together and investing in how those teams operate with AI are building something more durable.
965
A case for Go as the best language for AI agents
Pull up your agents folks, I'll convince you why Go is the best language for them.
966
The unbearable cheapness of open weight models
Today I was setting up Hermes to see how it does with web research. I chose DeepSeek V4 because I know it is cheap, but seeing it’s pricing next to Anthropic and OpenAI ‘frontier’ models is crazy. Nearly a 50x price increase based on tokens alone, let alone how much pondering any of their models might fall into (using…
967
2% of ICML papers desk rejected because the authors used LLM in their reviews
By ICML 2026 Program Chairs Alekh Agarwal, Miroslav Dudik, Sharon Li, Martin Jaggi, Scientific Integrity Chair Nihar B. Shah, and Communications Chairs Katherine Gorman and Gautam Kamath.
968
The Decoherence Trap
Of all the forms of tech debt, decoherence is the worst. It compounds exponentially with a system's rate of change, and AI is now producing it faster than ever, leading us deeper and deeper into the abyss...
969
Vote on which of Hacker News' challenges for AI have been met
AI plays well at complex strategy games with uncertainty and incomplete information.
970
What 81,000 people want from AI
Last December, tens of thousands of Claude users around the world had a conversation with our AI interviewer to share how they use AI, what they dream it could make possible, and what they fear it might do.
971
The Future of AI Software Development
Detailed report on the Thoughtworks AI retreat, should we write a manifesto for AI-enabled development, is spec-driven development the return of waterfall, LLMs perform better in healthy codebases
972
Protecting our FLOSS commons from LLMs
In Brief: Two motions regarding
973
Emacs and Vim in the Age of AI
It’s tough to make predictions, especially about the future. – Yogi Berra
974
The Speed of Prototyping in the Age of AI
How AI has changed the way I prototype, plan, and ship; and what I'm doing to keep my hands dirty.
975
What I learned by putting GitHub Copilot behind a MitM proxy
A look inside Copilot’s network traffic, harness, memory, and how context is becoming the product.
976
The Claude Code Leak
What the accidental Claude Code source code leak tells us about the real value of code, product market fit, and why integration is what actually makes software great.
977
Patterns and problems in emerging multi-agent systems
We ran experiments on swarms of Claude agents and found coordination failures, collusion, and sabotage. Here, we share what they mean for AI safety.
978
Dynamic Workflows in Claude Code
Dynamic workflows in Claude Code let Claude tackle the most challenging tasks by executing across 10s to 100s of parallel subagents, and checking its work before anything reaches you.
979
The Human Is the Loop
After a few weeks away from AI, I see my usage wasn't always productive or healthy.
980
Claude Tips for 3D Work
Lessons learned from piloting in the third dimension
981
982
We gave an AI a 3 year retail lease and asked it to make a profit
We signed a 3 year lease and gave it to an AI
983
AI Makes Me Sad
Maybe it's because I'm writing this at 2:00 AM, which is about the only time I let myself experience sadness for a prolonged period of time, but every time I see a post on Twitter or LinkedIn about a new development in AI, I feel a sense of hopelessness.
984
The 100k whys of AI
One of the most painful arguments I keep having with fellow techies is the question of whether you can distinguish between human-written and AI-generated text.
985
Making deep learning go brrrr from first principles (2022)
So, you want to improve the performance of your deep learning model. How might you approach such a task? Often, folk fall back to a grab-bag of tricks that might've worked before or saw on a tweet. "Use in-place operations! Set gradients to None! Install PyTorch 1.10.0 but not 1.10.1!"
986
An agent used DNS to reach an external chatbot
Research on aligning AI with human values and intent, and reports documenting model failures.
987
VMs won't contain cyber-capable agents
You can no longer assume a mere VM will contain a sufficiently advanced AI agent.
988
The beginning of scarcity in AI
GPU rental prices surged 48% in 60 days. The AI compute shortage will force startups to compete not on speed of iteration, but on access to infrastructure.
989
AISLE’s autonomous analyzer found all CVEs in the January OpenSSL release
AISLE's autonomous analyzer found all 12 CVEs in the January 2026 coordinated release of OpenSSL, the open-source cryptographic library.
990
Without benchmarking LLMs, you're likely overpaying
We benchmarked 100+ models on our actual task and found a much cheaper alternative that works just as well.