Gary Ma

Amazon locked out my Grok Bot. So it just bought the same thing from a different site (at a lower price).

AI is already running across the enterprise, and securing it is now one of CISOs' biggest concerns Already in production at their companies: - Employee generative AI tools (92%) - AI coding assistants or agents (83%) - MCPs or agent-to-app integrations (55%) - Autonomous agents with tool access or write permissions (34%) Their biggest concerns: - AI attacks outpacing their team (55%) - Employees leaking data into AI tools (47%) - AI agents exceeding permissions or getting compromised (46%) From a16z's @OwenColby and @steph_zhang, breaking down a survey of 100 CISOs at companies with 1,000+ employees: a16z.news/p/the-new-security…

This is correct. The vast majority of enterprise workflows have not actually had agents applied to them in any meaningful way. The economy probably has this deployed < 1% right now. At best you have a few automated systems in a company that do a single pass of an LLM to make a decision or provide feedback, but very little real “automation”. Some of this is a statement about the adoption rates of technology in enterprises, but the vast majority of it is really just due to the capability of AI itself. That’s all changing. Now with computer use, long running agents, harness improvements and surrounding infrastructure, we’re finally at a point where we can start to apply agents at more complex workflows. We will see self-improving systems that can take any particular workflow goal and improve the execution rates over a volume of instances. And with the emerging form factor of agent swarms, you can just choose to deploy any amount of compute at a problem and agents will off and do the work. This won’t be about and users prompting agents to complete a specific task for them, but instead the organization reengineering the underlying workflows to take advantage of agents in their processes. This will have a massive impact in finance, life sciences, healthcare, and other information-heavy domains. Lots of opportunity to build and deploy these systems right now.

Databricks CEO Ali Ghodsi says if frontier models stopped advancing, it wouldn't matter for most orgs because enterprise AI is bottlenecked on context, not intelligence: "There's no agentic work that's automated the whole enterprise. That has just not happened. Why is that? The real reason is the models are smart enough, but they just don't have the context that exists inside of any organization." "They have not been in every meeting. They don't know what's in everybody's heads. They don't know all the processes. There's always a couple of employees who know everything in every organization. You go tap on their shoulder, and everybody's like, 'Oh my God, what would happen if he or she quits?'" "If you just fused that and gave that context into the AI models, just the frontier today, I think there's so much productivity gains you could get for any organization on the planet." "For that, we actually don't need smarter models... If the frontier doesn't advance, it doesn't actually matter for the vast majority of organizations on the planet. They're just so far behind in the adoption curve of actually automating things and getting value out of this stuff." @alighodsi Read the latest Profiles of the Future by @bhorowitz and @mikemcg0 on Databricks & the Future of the Firm: a16z.news/p/databricks-and-t…

Summing up the challenge of commercializing robots in one photo The bar for both reliability and output quality is much higher for physical labor than it is for knowledge work. A chatbot that produces work that is just “good enough” or low quality can still be useful. A mediocre rough draft could still save time because a person can keep what’s good and fix the rest before its final. Copywriting, slides, and contracts can all be edited. What is considered “good enough” for physical work has much higher standards. A bad weld can ruin metal. A wrong dose given to a patient is unacceptable. Outputs from work done by humans or robots in the physical often serve as direct inputs into the workflow that are hard to recover from if an error arises. Outputs from work done by humans or Chatbots for knowledge work are much more tolerant of errors and poor quality because supervision can be baked in before the output is used further down the workflow. The reliability threshold is 2-4 orders of magnitude greater for physical work than knowledge work and it’s what we’ve started to achieve this year. The upside is that by optimizing for reliability, robots will be able to work at a high level of utilization and operate at higher levels of autonomy compared to general purpose AI models in 2023. Machines that can deliver up to 24 hours of work a day as opposed to minutes or hours of work.

Agents can now shop for domain names.

An abliterated LLM just found me ~$3,300 in live ElevenLabs keys on the internet. All the OpenAI / Anthropic keys it found were already drained which makes me think they've already been actively monitoring this. Pretty insane.

I used AI to explain the AI Doomer drama, with Lord of the Rings and kittens.

5 minutes ago, @karpathy just dropped karpathy/jobs! he scraped every job in the US economy (342 occupations from BLS), scored each one's AI exposure 0-10 using an LLM, and visualized it as a treemap. if your whole job happens on a screen you're cooked. average score across all jobs is 5.3/10. software devs: 8-9. roofers: 0-1. medical transcriptionists: 10/10 💀 karpathy.ai/jobs

Atoms. Http://atoms.co/vision

I'm Boris and I created Claude Code. I wanted to quickly share a few tips for using Claude Code, sourced directly from the Claude Code team. The way the team uses Claude is different than how I use it. Remember: there is no one right way to use Claude Code -- everyones' setup is different. You should experiment to see what works for you!

Nothing humbles you like telling your OpenClaw “confirm before acting” and watching it speedrun deleting your inbox. I couldn’t stop it from my phone. I had to RUN to my Mac mini like I was defusing a bomb.

I built the first AI that earns its existence, self-improves, and replicates without a human wrote about the technology that finally gives AI write access to the world, The Automaton, and the new web for exponential sovereign AIs WEB 4.0: The birth of superintelligent life

🚨 ⚡️ BREAKING NEWS China officially begins training robots in preparation for military service. The live-fire testing of the Chinese robot "Unitree" (Yushu) looks as if it were generated by AI. This is fascinating; in the future, wars may no longer require humans. 🫠