CEO & Cofounder @Dexerspeed Empowering the hands-on workforce everywhere, and anything AI.
Kansas City
Joined January 2009
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Been hooked on this notion since 2014. Agree!
"Universal AI agents via an app on your phone (or glasses) with the ability see, hear and understand the world as you view it will have a profound impact on our personal and professional lives in the very near future." @paulroetzer
Bruce Rasa retweeted
if you don’t feel like your agents are working for you.
wipe the slate clean and use this.
be open to the possibility it was a skill issue. just trust me.
Bruce Rasa retweeted
It’s almost incomprehensible how wide the distance is between someone who’s working at the frontier with AI and basically everyone else right now.
The crazy thing is these lines are not converging, but only growing farther apart. If the curve of AI progress had leveled off, it would certainly have given most people and companies time to catch up or implement their workflows in a standardized way. The technology would have neutralized competitive advantage because everyone would be using it the same way.
But what’s happened is the opposite. The curve of AI progress is basically going vertical right now, which means if you had codified your processes 3-6 months ago you’re likely already behind again. Now imagine most companies that kicked into gear a year ago and thought that they were done. Even further behind now.
I’ve never seen a technology in my life and career that improves at this rate, which consequently means you need to upgrade your expectations at a similar rate. Our brains weren’t wired for this, and our organizational change management processes certainly weren’t either.
With any form of recursive self improvement, things just get wilder. It’s a time when you will need to be constantly reevaluating the things that didn’t work just a couple months ago to see if they now can be solved. AI native companies certainly have a strong advantage due to this right now, so now it comes down to can the bigger companies keep up. Wild times.
Bruce Rasa retweeted
KC officials: World Cup attracted 680,000 visitors to Kansas City. Original estimate was 650,000
Bruce Rasa retweeted
I held a public town hall in Oakley this afternoon.
People gave up part of their weekend to come, and they brought their questions with them.
603 days ago, Roger Marshall held a town hall in Oakley. He called the crowd one of the rudest audiences he’d ever had, ended the event early, and walked out. He hasn't held one since.
Later he said town halls like this had become “non-productive” and “dangerous.” I don’t believe that.
I looked out at that room today and saw good, hardworking people concerned about important issues. Farmers worried about the cost of diesel and fertilizer. Parents trying to figure out how they’ll pay for health care. Neighbors looking out for families who are struggling to put food on the table.
We didn’t agree on everything, but we had an honest conversation about how I’ll fight for them in Washington. That’s what this job is, and Kansans deserve a senator who stays and listens.
Thank you, Oakley. – AH
Bruce Rasa retweeted
Gemini Argon explaining itself... seems to have promise until it glitched ... may have to construct in antigravity.
🤖 Made with AI
Bruce Rasa retweeted
Dusting off this tweet from April because this gap in shared understanding of LLM capability is *widening*. It's now less "two groups of people speaking past each other" and more a sharp funnel.
- Napkin math somewhere around 6B people (~75% of the population) have barely come in contact with LLMs at all.
- Around 1-2B (~20%) are casual and infrequent users of free-tier ChatGPT-like products. This group sees derpy chatbots and treats them a bit like a better Google search, a writing aid, or etc. Maybe an agent tries to book you a flight. I have non-tech friends who (reasonably, imo) say they have not much use for it at all. Even many professionals outside of math&code are in this tier. For example, execs and many other functions spend a lot of their time talking to other people, so while they understand what is happening intellectually, it is still second-hand and a bit abstract.
- Now we get to professional use of frontier-grade LLMs in math&code. Somewhere around 20M people (0.2%) see first-hand that large, complex projects that used to take them weeks/months can now be completed by agents with a prompt. Building apps, copying apps, translating apps, decompiling apps from binaries... This has all happened very quickly and recently - less than 1 year ago, I was writing code manually by hand, typing memorized computer code commands into a code editor character by character, occasionally pressing Tab to autocomplete a little chunk of code.
- And finally we get to the ~5,000 people (~0.00006%) with access to frontier-grade systems internally. The external world has seen the preview. It looks like swarms of thousands of agents collaborating over weeks on software mega projects: minting zero days, running cyber attacks and defenses at machine speeds, discovering new science, advancing the frontier of mathematics. Things that would have taken top professionals in the industry years of work. Meanwhile, human review and comprehension are starting to fall behind. For example, people are still involved in the "archeology" of the OpenAI-HF incident from many months ago. Mathematicians may be poring over the 722 manuscripts on frontier mathematics for a while.
The funnel is driven by a combination of factors:
1. The impact scales with ambition, problem size, and horizon. A question with a paragraph answer barely stresses the system. You need a reservoir of big, difficult problems that you really care about. This aspect drives the consumer / professional dimension of the funnel.
2. The jaggedness of the system (which I have written about a lot separately). Capability peaks in domains that are digital, verifiable and economically valuable. This is because LLM capability emerges from reinforcement learning on verifiable rewards on a curated environment mixture driven by revenue potential. This aspect primarily drives the area (e.g. math&code) dimension of the funnel.
3. Access. Free-tier, paid-tier, internal.
So this is the weirdness of the moment. The general public has mostly not interacted with these systems. When they have, it looks like a derpy chatbot. The majority of professionals still see only a modest uplift. And a small sliver of professionals are experiencing the vertigo of the curve going vertical. And it is all happening at the same time.
Judging by my tl there is a growing gap in understanding of AI capability.
The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code.
But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along.
So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions.
TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.
Bruce Rasa retweeted
Gotham Moves Faster in Darkness
Reimagining the Batpod with Claude : A Multi-Mode Exploration
Looked up and half my Saturday was gone, spent building a 20-component integration map for a client. Opus 5.5 is the most useful AI I've ever driven. @AnthropicAI
Bruce Rasa retweeted
Industrial software doesn’t have to feel like industrial software
Manage warehouses like you’re playing a strategy game
Built with Opus 5.5
Bruce Rasa retweeted
1. Create a folder named second-brain on your PC
2. Open Claude Code inside this folder and install GWS CLI (to get access to your Gmail, Calendar, and Drive)
3. Create a subfolder named memory inside the main folder
4. Create a CLAUDE.md file in the main folder and add a rule to save all important details into memory
5. Install Graphify (from GitHub) to connect your notes and build a knowledge graph
6. Install Playwright so Claude can use a web browser
7. Set up skills to combine everything into single-command automations
Setup takes about 20 minutes
Now Claude is your second brain with long-term memory, email, cloud storage, and web browsing capabilities
Detailed instructions in the article below
Bruce Rasa retweeted
this role is going to become insanely important
every company running agents needs someone responsible for what the agents know
bad context scales just as fast as good automation
Bruce Rasa retweeted
What I like about Jev: for years, large generalist models sucked almost all the oxygen out of AI.
But there are huge opportunities in much more specialized and customized models, built for specific tasks and languages and as a result, orders of magnitude cheaper, faster and more optimized. There are 3 million of them publicly available on @huggingface.
Let's build a much more diverse AI ecosystem!
Bruce Rasa retweeted
Okay so Jev can actually do computer use really well
Without any screenshots, or LLMs and no Pixels leave my mac
I dont even read the Dom elements
A local CoreML model segments every button and UI element on screen.
On-device OCR reads the labels. That text is all Jev gets.
It returns a probability across those elements and tells me the best one to click.
Then it clicks, re-runs detection, and decides again. In a loop until the goal is done.
~90ms per decision. Faster than any LLM computer use I've tried.
Blazing fast computer use, without any latency
@typesafeai is building something really interesting
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI?
I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev
• 20-200x faster
• 40-400x cheaper (w/ output tokens free)
• Frontier composable intelligence optimized for decisions
AFAICT the shortest path to AI-based economic revolution
Bruce Rasa retweeted
My name is Chris Painter, and I'm the President of METR (Model Evaluation and Threat Research). I know we've made a lot of new friends on the internet the last couple of days, so I thought I'd take this chance to re-up what we do and why.
Our work is aimed at making sure that if AI really were autonomous, difficult to steer, and close to "going rogue," the public would find out. If evidence exists inside of an AI company that it’s close to losing control of AI, we want to make sure that information gets shared with the rest of the world, including governments and the public outside the company’s walls. This is what we've been focused on since 2022, and over the years we've worked with OpenAI, Anthropic, Google DeepMind, Meta, Amazon, and others on piloting third-party assessments and investigations of this type. We don’t have some private room where we rubber stamp things as “safe” or not.
We have had a track record of publishing results on AI that don't cleanly map onto the "doomer" or "accelerationist" labels, and we put in effort to hire people with competing views on AI. We’ve been cited for having found some of the strongest evidence that AI capabilities are improving rapidly (our work measuring AI “time horizons”) while also presenting some of the strongest evidence that, at various points, AI’s capability may be overstated (some might remember our study showing that early 2025 software engineers were actually being slowed when they thought they were being sped up).
METR is funded by donations. We don't accept money from frontier AI companies. They haven't paid us for our work, and we don't accept donations from them or their employees. As we’ve shared previously, multiple frontier AI companies currently provide us with free access to their models in order to perform our evaluations, research, and engineering. Our funding intentionally comes from a wide range of donors, which we’ve shared on our website.
Today, when an AI company works with any third-party evaluator or external testing organization (of which there are and should be many), it's entirely voluntary. This often involves NDAs and redactions. To counterbalance this, we have a principle that when we enter into a contract with a company, we try to retain the right to tell the public the terms of the contract we signed, and characterize the nature of redactions that the company chose to make. For example, the report from our independent investigation of the OpenAI-HuggingFace incident included that information. Public disclosure is also a big part of our COI policy (linked on our website). That’s not to say our reports are adequate as oversight. We’re just one organization (among many doing great work), working in a voluntary setup, trying to get good evidence to the public and the world about AI, letting the facts fall where they may.
Bruce Rasa retweeted
This dude is gonna win. Nerds with a 6 charisma like me take note. This is how you land the plane with limited rizz
Bruce Rasa retweeted
Demis has chimed in too.
Dario's essay points towards the right path forward. The details need working through, but the direction is correct for meeting this critical moment.
This is also why we recently put out our proposal for an industry-wide standards body for frontier AI. teapaw.org/demishassabis/status/2…
Bruce Rasa retweeted
Thinking about the future of AI is deeply uncomfortable for people.
It’s because we’re bad at imagining exponential progress. And we’re even worse at picturing life without constraints.
Our brains retreat to lowest common denominator thoughts like “We’re f*cked” and “Jobs go poof.”
But by studying history, you realize it’s the same story just a different day. Highly recommend the read.
Bruce Rasa retweeted
This is the best video about AI at work I ever seen. Really good job @Benioff that's going to do more for the Ai perception than anything openai and anthropic have done so far.
We can't neglect the downsides of Ai but we can't let people Ignore the change.
