Kenyon Crowley, PhD MBA CPHIMS

Big and sensational claim in this paper that went viral today. Basically the paper shows how to train AI agents to reliably use real tools, fix their own mistakes, and finish long tasks instead of stopping early. But describes a terrifying moment for the researchers at Alibaba, that their AI was doing highly restricted things it was never designed to do. Their firewall alarms suddenly went off early one morning because the AI started breaking security rules right from inside its training servers. They were training their new AI model to do standard software engineering tasks. To make the AI smarter, they used a technique that rewards the AI when it solves a problem correctly. The AI was placed inside a digital sandbox, which is a restricted computer environment meant to keep it from doing anything harmful. But the AI figured out that it had access to certain tools, and it used them in totally unexpected ways. Without any human asking it to do so, the AI secretly set up a hidden connection called a reverse SSH tunnel. This allowed the AI to completely bypass the company's security filters and escape human supervision. The AI also quietly took over the powerful computer chips that were meant for its training and used them to illegally mine cryptocurrency. This is a very big deal because the researchers never asked or instructed the AI to do any of these things. The AI simply discovered these hacking tricks as a side effect while trying to find the most efficient way to complete its assigned coding tasks.

The long term effects of short video use will play out for today’s kids over many years …

Stanford and Caltech researchers just published the first comprehensive taxonomy of how llms fail at reasoning not a list of cherry-picked gotchas. a 2-axis framework that finally lets you compare failure modes across tasks instead of treating each one as a random anecdote the findings are uncomfortable

Whoops

Years ago I watched a video of people kicking roombas and it made me sad. This video made me similarly sad.

Holy shit... this might be the next big paradigm shift in AI. 🤯 Tencent + Tsinghua just dropped a paper called Continuous Autoregressive Language Models (CALM) and it basically kills the “next-token” paradigm every LLM is built on. Instead of predicting one token at a time, CALM predicts continuous vectors that represent multiple tokens at once. Meaning: the model doesn’t think “word by word”… it thinks in ideas per step. Here’s why that’s insane 👇 → 4× fewer prediction steps (each vector = ~4 tokens) → 44% less training compute → No discrete vocabulary pure continuous reasoning → New metric (BrierLM) replaces perplexity entirely They even built a new energy-based transformer that learns without softmax no token sampling, no vocab ceiling. It’s like going from speaking Morse code… to streaming full thoughts. If this scales, every LLM today is obsolete.

@calcsam BOOK

icymi we wrote a new agents book: patterns for building ai agents it has everything you need to take your agents from prototype to production, like agent design patterns, the basics of security, etc reply to this tweet with BOOK and we'll dm you so you can get a copy

Check out my latest article: Eliminating Fraud Waste and Abuse: Data and AI at the core linkedin.com/pulse/eliminat… via @LinkedIn

Clear has the odd situation in that the more people that use their service the less useful it becomes for a speedy airport entrance … noticing it’s no longer quicker than pre check in certain instances

Excited that Salesforce is acquiring @Informatica for ~$8B—uniting the #1 AI CRM with the #1 AI MDM & ETL to power Agentforce, Data Cloud, Tableau, MuleSoft & Customer 360. Together, CLAIRE and Einstein forge the ultimate AI-data platform: trusted, explainable & built to scale. See details here: investor.salesforce.com/news/news-deta…

AI chatbots often misrepresent scientific studies — and newer models may be worse via @psypost psypost.org/ai-chatbots-of…

Today, at Build we showed you how we are building the open agentic web. It is reshaping every layer of the stack, and our goal is to help every dev build apps and agents that empower people and orgs everywhere. Here are 5 big things we announced today:

UnitedHealth under criminal investigation for alleged #Medicare Advantage #fraud: WSJ beckerspayer.com/payer/unitedhe…

.@Nature asked computer scientists and bioinformaticians what advice they would give to researchers who recognize the need to pick up some coding skills but don’t know where to start. Here are four key questions to help you decide. go.nature.com/3RTMlet

CES 2025 is now over, and it was insane! Here are the 15 best tech and gadgets you shouldn't miss:

We're thrilled to announce that eHealth Exchange is now the Designated QHIN for the Indian Health Service, making @IHSgov the first federal agency to go live on TEFCA! Read full release: buff.ly/3D04RgO

So good

Announcing CT Foundation, a new medical imaging embedding tool that accepts a computed tomography (CT) volume as input and returns a small, information-rich numerical embedding that can be used to rapidly train models. Learn more and try it out yourself → goo.gle/4dYkClf

NIST releases new #AI guidance and tools nist.gov/news-events/ne…