rob (@FieldToFuture) header
rob (@FieldToFuture) profile picture

Building @Recertia | AI RL Researcher @georgiatech

SF
Joined October 2012
Photo by rob (@FieldToFuture)Photo by rob (@FieldToFuture)Photo by rob (@FieldToFuture)Photo by rob (@FieldToFuture)Photo by rob (@FieldToFuture)Photo by rob (@FieldToFuture)Photo by rob (@FieldToFuture)Photo by rob (@FieldToFuture)Photo by rob (@FieldToFuture)Photo by rob (@FieldToFuture)
rob retweeted
This is f*cking insane. Geoffrey Hinton, the Nobel Prize winner they call the Godfather of AI, was asked what AI will do to jobs. His answer: "For mundane intellectual labor, AI is just going to replace everybody" In 93 seconds, he explains why this time is different: one person with an AI assistant will do the work of 10 The new jobs everyone promises? If AI can do all routine thinking work, he asks what jobs are left to create Then the part that hits hardest. His niece answers complaint letters for a health service. Each one took her 25 minutes. Now AI writes it, she checks it, and it takes 5. So they need five times fewer of her He agrees it won't be AI that takes your job, it'll be a person using AI. That just means far fewer people 10 People → 1 Person + AI → Agents → Harness → Loops → The One Who Stays Save this before it disappears from your feed Everything below is free: A free AI course for non-programmers elementsofai.com AI Python for beginners, taught by Andrew Ng learn.deeplearning.ai/course… Interactive prompt engineering tutorial github.com/anthropics/prompt… Starter projects you can deploy with Claude github.com/anthropics/claude… The OpenAI cookbook github.com/openai/openai-coo… An open-source agent that runs on your machine github.com/aaif-goose/goose The open-source coding agent github.com/anomalyco/opencod… Gemini in your terminal github.com/google-gemini/gem… Open-source AI developers github.com/OpenHands/OpenHan… Build resilient agents as graphs github.com/langchain-ai/lang… Microsoft's agent framework github.com/microsoft/autogen Secure sandboxes for your agents github.com/e2b-dev/E2B Let your agents use any website github.com/browserbase/stage… Be the one person who runs the AI, not one of the nine it replaces 95% will wait to find out if their job is next, the 5% who build a harness will be the one doing the work of ten Bookmark it and start with the first link tonight Then use the guide below to build your harness before your job gets automated ↓
Your agent loop is probably a cron job with your credit card Researchers checked 36,487 repos. Nearly all loops had a trigger. Far fewer had a check, state or an exit What's missing across the harness, the loop and the graph ↓
19
69
2
402
159,482
I'm an accelerator, a founder house, a program. The name doesn't matter, here is what I am: 8 weeks in San Francisco to build the foundations of a generational company - non-US based founders - pre-idea, pre-team - 40 spots - $250k investment for the best teams what I cover: flights / housing / food / visa support / co-founder matching / personalised support / network access by Entrepreneurs First backed by Patrick & John Collison, Demis Hassabis, Daniel Gross, Nat Friedman, Reid Hoffman, Eric Schmidt & others alumni have built: Cleo, Aztec Network, Gensyn, PolyAI, Neptune Robotics, Magdrive Comment your edge ! Our next cohort is open now
261
61
11
861
176,540
San Francisco has one of my favorite surf spots in the world. Just took this shot
45
32
8
841
81,276
This is f*cking insane. OpenAI co-founder Ilya Sutskever went back to the University of Toronto and told the graduates this: "The day will come when AI will do all the things that we can do. Not just some of them, but all of them Anything which I can learn, anything which any one of you can learn, the AI could do as well" In this 9-minute speech, he explains why your brain is a biological computer, and why a digital one will learn everything it can Neural Nets → AlexNet → ChatGPT → Safe Superintelligence → AI That Can Do Every Job His advice for living through it: accept reality as it is, don't waste time regretting the past, and keep asking what the best next step is "You may not take interest in AI, but AI will take interest in you" The people who watch what AI can actually do, not the hype, will be the ones who know how much time they have Worth more than any $5,000 AI course Bookmark it and watch it tonight Then read how to put AI to work for you before it takes the work in the harness engineering guide below ↓
Your agent passed every test The issue is still open A better prompt won't fix it, because the model isn't the broken part I broke down the harness, loop and graph around it: what each one owns, how they nest, and which one to fix first ↓
54
115
16
992
139,701
We're giving away a Hogwarts Legacy custom wrapped NVIDIA GeForce RTX 5090 to celebrate its official release with DLSS 5 🪄 To enter: 🟢 Share this post 🟢 Comment #RTXON Terms and Conditions: nvidia.com/en-us/geforce/con…
84,345
71,871
7,630
67,352
5,791,910
Elon called it out: SoftBank is defaulting on their turbine orders. I suspect the main reason is what I repeatedly pointed out for months: 1. SI demand is going through the roof. There is no bubble. 2. The real problem is supply. 3. Supply has multiple layers: a) Energy b) Land and permits c) Buildings d) Chips & memory e) Building the superclusters f) Financing a) has become the #1 problem, and only Elon can solve it. You need to literally manufacture your own turbine blades. OR you have to find a place where there is enough excess energy AND an entity that is able to do the right kind of deal - which is possible but very hard. b) this is becoming harder but is not the primary problem. Going forward, it requires pitching local communities, offer very good deals to the actual people living there and making sure everyone is happy, which requires a new skillset c) Buildings = easy d) Getting access to large clusters of chips AND memory requires large-scale projects (50B+) AND a strong reputation that you will get it done and pay. Not many entities or people can secure supply from Nvidia and Micron. e) one of the most underrated problems: you have to actually build these things with hundreds of thousands of perfectly calibrated GPUs, etc. - you need a lot of rocket scientists for that, or face years of delay and massive cost explosions f) you need access to tens of billions of money , meaning flawless credit profile OR a pile of cash you are sitting on OR a deep equity market profile. Put these together - and you will see this game is one that can only be done by AWS, META, MSFT, GOOG and SPCX... AND that SPCX will have a 2-4x speed advantage, wich translates into tens of billions saved in interest and faster ROIC cycles. +++ In short: MASSIVE demand overhang that is getting WORSE over time. TRILLIONS of margin to be generated over the next 5 years. A HANDFUL of companies who can stand up the supply. SPCX getting the lion share of it. /C /Compute buildout.
Replying to @KatieMiller
SoftBank is defaulting on their turbine orders
71
195
12
1,840
202,243
Acclaimed asian megastore T&T Supermarket opens at site in San Francisco that Whole Foods previously abandoned due to “nightmarish”permitting delays and had been vacant for a decade This time around the permitting was fast
8
9
4
433
17,863
#New: What it costs to rent in the Bay Area (med 1BR): San Francisco: $4,430 Mtn View: $3,730 Palo Alto: $3,570 Sunnyvale: $3,240 Santa Clara: $3,220 San Mateo: $3,200 San Jose: $2,890 Berkeley: $2,290 Oakland: $2,120 Hayward: $1,980 Source: @Zumper
11
34
12
285
35,368
And electrical equipment, cooling, networking and batteries
Elon Musk says the AI boom will hit a WALL by the end of 2026. He says the whole industry is about to learn a hard lesson in hardware. Chip output is exploding, but electricity is nearly flat everywhere outside China. So the two lines cross this year. He says by the end of the year, we will be making more AI chips than we can actually turn on. Millions of them pile up with nowhere to plug in. In his words, the bottleneck for the next year is not chips, it is raw power. Whoever can turn on the most chips fastest wins the race. In the end, the AI race comes down to one thing: Raw electricity. — Elon Musk (.@elonmusk) on Dwarkesh Patel's (.@dwarkesh_sp) podcast
2,364
4,639
404
46,721
5,393,058
rob retweeted
How to trap Sam Altman:
149
2,213
55
36,760
286,339
New Tsinghua and Microsoft paper finds that DeepSeek Harness used 87.93% fewer tokens than its original version on 98 HumanEval tasks while success rose from 71.43% to 85.71%. Agent tools like Codex and DeepSeek Harness call the LLM after each tool result to choose the next step. Often that step was already decided, like running tests once the code compiles. HarnessMM lets the model write future commands with exact arguments, plus a check for each, such as a successful build. When a tool result passes the check, the agent runs the command and skips the LLM call. On 98 HumanEval tasks, Codex kept its 90.82% success while using 29.54% fewer tokens than plain Codex. DeepSeek Harness rose from 71.43% to 85.71% success and used 87.93% fewer tokens than the original. If your agent runs predictable chains like write, build, test, have the model plan them once with pass checks instead of re-asking each step.
78
36
8
272
14,340
rob retweeted
SITUATION DETECTED: Researchers at MIT show that GPT-6 Astra can natively read and write neural network weights through pure reasoning - no gradients, no training loops - calling it Weight-Space Programming.
124
495
129
8,933
431,194
First in my bloodline to use a quantum computer It's easier than you think: > Create an account at @IBM Quantum Platform > Create an Open Plan instance and copy its CRN > Generate an API key from the dashboard and keep it private. > Install Qiskit and IBM’s runtime package: pip install qiskit "qiskit-ibm-runtime>=0.50.0". > Build your circuit in Python, connect using your API key and CRN, and select a real quantum computer. > Submit your circuit, track it under Workloads, and retrieve the measurement results when it finishes
25
66
7
836
29,361
If you look closely enough, breakthroughs in everything are accelerating exponentially. An exponential always starts off looking small.
this might be my last normal tweet before biotech goes vertical i'm not a whistleblower. I don't work at Lilly, Novo or any of the big labs but there is a massive shift happening in human biology right now. it's sitting in press releases and almost nobody reads them the last 6 months alone: - a once-daily pill roughly doubled median survival in metastatic pancreatic cancer (13.2 vs 6.6 months) - a one-time gene editing infusion cut hereditary angioedema attacks 87%, and 62% of patients stayed attack-free and off all other prevention for 6 months - a one-time gene edit for cholesterol dropped LDL up to 62%, and it held for over a year - a personalized mrna vaccine beat keytruda alone in a 1,137 patient melanoma phase 3 - retatrutide hit ~28% weight loss in a phase 3 - an ai-designed drug entered phase 3 - a pill that regrows hair passed its second phase 3 - an immunotherapy that could let some rectal cancer patients skip surgery, chemo and radiation just got fda approved - a man lived 271 days off dialysis on a pig kidney - human cells were caught passing chromosome-sized chunks of DNA to their neighbors, and it changes how the neighbors behave we are on the verge of an era where the human body is a software problem and the update cycle gets shorter everyday stick around, it's going to get weird bio/acc
2,290
6,277
568
67,739
5,912,919
Replying to @FieldToFuture
Unfortunately, I think it is likely a major change to the software development career option. Oregon State University has seen a -23% drop YoY in computer science enrollment. Oregon State U. Put Its Chips on Computer Science. Then the Bottom Fell Out. archive.is/UKvr9 Nationally, computer science enrollment has fallen by 53,000 students. archive.is/7hNMN
1
1
217
Home prices in San Francisco are soaring. But it's just a handful of ZIPs—in SF proper and Silicon Valley—that are hot. Prices in the broader SF-Oakland-Fremont metro area are up only ~3% (not spectacular in a national context). My map:
31
13
7
270
58,703
Prices in Osaka and Bangkok are ~same despite 4x wage difference. I knew Japan was cheap these days but WOW. And Japan has all the standard First World attributes like drinkable tap water, clean air, safe roads. Explains why everyone and their dog are going to Japan in 2026.
🤖 Made with AI
106
106
26
1,199
103,462
Vietnam plans to offer 0% income tax for 5 years to the people it needs for its biggest projects. Overseas Vietnamese can qualify. People would be picked on merit: degrees, titles and years of service would not be required.
2
10
2
103
10,453
A diferença entre o Comunismo e o Capitalismo.
608
4,618
223
22,067
1,375,509
Recursive Self-Improvement
A retired NASA engineer who had worked on the Space Shuttle program for 25 years was hired by SpaceX at age 62. He described the first week as the most disorienting experience of his professional life. At NASA, a design change required 3 meetings, 2 committees, a review board, and 6 to 18 months of documentation. At SpaceX, his new supervisor said "if it works, build it. If it doesn't, change it by Friday." He sat at his desk after the first day and called his wife. He told her he felt like a man who had been swimming with ankle weights for 25 years and someone just cut them off. He could move. He could decide. He could build something in the morning and test it in the afternoon. The constraint that he had accepted as the nature of aerospace engineering turned out to be the nature of bureaucracy. Within 6 months he had contributed to more design iterations than he had completed in his last 5 years at NASA. Not because he was working harder. Because the time between having an idea and testing the idea collapsed from months to hours. The same brain. The same knowledge. A different operating system. He described a specific moment where he proposed a modification to a Raptor engine component. At NASA, the proposal would have entered a queue. At SpaceX, the modification was machined by the end of the day and tested by the following morning. He watched his idea become a physical object in 18 hours. At NASA, 18 hours would not have been enough to schedule the first meeting to discuss whether to schedule a meeting. He told an interviewer: "I didn't get smarter when I went to SpaceX. I got faster. The intelligence was always there. The system was in the way." The difference between SpaceX and NASA is not talent. NASA has extraordinary talent. The difference is the time between a thought and a test. SpaceX compresses it. NASA elongates it. The same engineer produces 10x more at SpaceX than at NASA because the bottleneck was never the engineer. It was the meetings about the meetings about the work.
1,068
3,903
218
52,341
5,100,934