Every 📧
@every ·
Mike as a service. Coming soon.
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People and companies shaping AI. Filter your watched accounts, catch up on recent posts, or find the most liked and viewed.
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209 watched accounts · 2893 matching posts · Showing up to 3,000 recent stored posts. Counts are snapshots, not live X totals. This page refreshes every minute while visible. Last collected .
dax@thdxr ·
is now a good time to get into cybersecurity insurance
Gabriel Chua@gabrielchua ·
i like when my dot manages my codex cloud threads throughout the night
Ben Tossell@bentossell ·
i expanded on this in my newsletter today and getting lots of responses
i rarely promote my newsletter but here’s the link if this tweet struck a chord
https://open.substack.com/pub/bensbites/p/ai-is-overwhelming-and-im-doing-it
Ben Burtenshaw@ben_burtenshaw ·
It was super fun to learn how @MistralAI built le chonk from the ground up in Europe in their own datasets. Why it excels at cyber. And why we should start building with it.
Allie K. Miller@alliekmiller ·
I’ve been texting with my OpenAI Dot for awhile and prefer it over the app.
Favorite use case is just screenshotting something, texting it to Dottie, and give instructions.
“Add to cal” “Handle this” “Ask Austin if he wants to go with me” “Add to my bucket list” “Explain this” “When can I do this?” “What will this conflict with?” “Remember I have to do this”
Also recommend asking it to make a contact photo. See below for Dottie the Dalmatian.
Alex Imas@alexolegimas ·
This is such an incredibly creative project.
- Every 📧
@every ·
Very little is free in NYC. But if you're a paid Every subscriber, our afterparty for Thesis: 2027 costs exactly $0.
Your agent can work late. You have a party to go to. DJ. Passed bites. Open bar. And more.
🥳 Join us at Pioneer Works in Red Hook, Brooklyn.
🪩 November 5, 2026. 6–9 p.m. ET. 21+.
Peter Gostev@petergostev ·
Gemini 4 Carbon, Genie 4, AA index 5, Anthropic IPO, 6.1 Terra & more AI https://x.com/i/broadcasts/1NGarobEZPRJj
Dean W. Ball@deanwball ·
I occasionally run into fortune 100 firms that have not adopting coding agents *at all.* adoption is still very very early.
- Dean W. Ball
@deanwball ·
"Yeah, people talk a lot about RSI as AI that does AI research. There's very little talk about self-replicating data centers, this idea that you can use AI to control robots and run fabs and build turbines or solar panels and build data centers. But I think we have that within grasp."
Samuel Hammond 🦉@hamandcheese ·
If any crash is coming for the stock market its for everything that's still radically mispricing strong AI. There may also be an extreme "end of ZIRP"-like tide-going-out effect on forms of hidden leverage that no longer make sense relative to the IRR of AI capex
Andrew Curran@AndrewCurran_ ·
I was going to post some new sama quotes from this interview this morning, but prinz already posted a great summary. I will add that this is the third time I've seen Mr Altman talk about self replicating OpenAI datacenters. The first use case for OpenAI robots appears to be building more OpenAI robots and building more OpenAI datacenters. Mr A also wrote specifically about this on his blog a couple of years ago.
'Yeah, people talk a lot about RSI as AI that does AI research. There's very little talk about self-replicating data centers, this idea that you can use AI to control robots and run fabs and build turbines or solar panels and build data centers. But I think we have that within grasp.'
Rhys@RhysSullivan ·
how life with cursor tab felt
Santiago@svpino ·
This is going to be massive for companies:
It's a service that sits between any AI software and the tools and model providers it uses.
The idea is to let the company control who uses what from a central location, for example:
• Control model access • Control model budgets • Control tool access • Control guardrails
- Samuel Hammond 🦉
@hamandcheese ·
Adam's doing the Lord's work
Riley Brown@rileybrown ·
As of today October 29th. This is my current AI Stack.
Mostly comprised of 2 agent tools, and 1 that allows me to centralize my plugins and skills which makes it easier to switch agent platforms.
- Samuel Hammond 🦉
@hamandcheese ·
This is with only ~50% adoption by the Fortune 500 and with very low spend. Diffusion is still incredibly early.
Harrison Chase@hwchase17 ·
browser use is one of the fastest growing agent primitives
get started with it in managed deepagents today!
Wes Bos@wesbos ·
We had really funny names for the flavours but they were nixed by the organizers 😩
Elon Musk@elonmusk ·
Our civilization would be winning wondrously if we are exploring the galaxy with Von Neumann probes by 2100!
Larry Page might be right. He has correctly predicted many things.
Anthropic@AnthropicAI ·
We’ve expanded our AI for Science program beyond individual teams to support some of the world’s leading scientific foundations, institutions, and research groups. https://www.anthropic.com/news/ai-for-science-expands-foundations-research-institutions
Riley Goodside@goodside ·
We’ve known since 2023 AI could not continue to improve due to “model collapse”—training on poisoned internet data generated by AI. This is why LLMs have made no progress since that time, steadily declining on all benchmarks, and are projected to disappear completely by 2030.
- Andrew Curran
@AndrewCurran_ ·
Really interesting work from Sauers.
biohub@biohub ·
400 million people live with a rare disease. Fewer than 5% have an approved therapy. Applications are open for Cycle 4 of Rare As One, funding patient-led organizations working on rare respiratory disorders, rare immune dysregulation disorders, and sarcomas. Apply by 12/15: https://bit.ly/RAO-cycle-4
- Elon Musk
@elonmusk ·
Interesting
- Alex Imas
@alexolegimas ·
I joined @GoogleDeepMind to develop a research program on the economics of AGI. Today, together with Andrew Koh (@andrewjkoh) and Shane Legg (@ShaneLegg), we are incredibly excited to release The Economics of Intelligence, the first in a series of projects from our group on how AGI will change the economy.
How do capability improvements transform the economy, and when? In this project, we define thresholds of economic capabilities, e.g., minimal AGI, based on how they transform the economy. We then track how the economy–market structure, employment, and wages–changes during the transition across capability regimes.
We have seen exponential increases in what AI agents can do but the broader economy seems almost remarkably unchanged. Part of the reason is that the solo AI agent is the wrong economic object; economic transformation is an equilibrium outcome where organizations compete. Looking at how intelligence functions within organizations, transformation will depend on when two key capability thresholds are crossed: competence (gains on individual skills, e.g., coding, math) and coordination (gains on ability of agents to cooperate and work together).
We show that what economic transformation looks like depends on whether AI becomes supercompetent, supercooperative, or both—the regime of artificial superintelligence (ASI). Tracking this transition shows why the real visible transformation may come from improvements in coordination—a capability most benchmarks don’t yet track. Past a certain threshold, AI capabilities can break the Coasian ceiling on firm size and lead to an economy that looks drastically different than the one we see today.
Two main takeaways: 1. To understand the path of transformation, we should be tracking agentic coordination more closely. 2. The impact of AI will likely show up in wages before market structure or employment.
We are really excited about this paper. Excited to hear people’s thoughts.
Link: https://institute.deepmind.com/essays/the-economics-of-intelligence/
Simon Willison@simonw ·
Fascinating case study of the sharpest edge of what you can do with agentic engineering in the Fable era - my eyebrows raised at least a dozen times while reading this
Shane Legg@ShaneLegg ·
Two new DeepMind Institute essays:
What is Work For? As AI advances how do people value their jobs, for material needs and beyond?
The Economics of Intelligence When will AI capabilities impact market structure, wages and jobs?
Read the essays here -> https://bit.ly/dmi_home
Artificial Analysis@ArtificialAnlys ·
Fish Audio Drama 3 is the #1 open weights model on both Artificial Analysis Speech Arenas, and #1 of all models on Pronunciation Robustness
@FishAudio has released Drama 3. We evaluated it across both Speech Arenas and our Pronunciation Robustness benchmark.
Key takeaways:
➤ Text to Speech, Provider Voice: Drama 3 scores an Elo of 1,278 across 1,512 arena appearances, ranking #6 overall and #1 among open weights models, 38 points clear of its own Drama 3 Preview at 1,240 and 50 ahead of BreezeBlue's Breeze TTS 2 at 1,228
➤ Text to Speech, Controlled Voice: Drama 3 scores 1,085 across 1,958 appearances, ranking #12 overall and #1 among open weights models, ahead of Ant Group's Ming-3.0-tts at 1,068 and its own Preview at 1,063
➤ Pronunciation Robustness: Drama 3 scores 94.6% across 2,157 rated spans, ranking #1, ahead of Ming-3.0-tts and Drama 3 Preview, both at 93.2%
➤ Speed: Drama 3 generates 66.6 characters per second, ahead of its own Drama 3 Preview at 60.7 and Murf's Speech Gen 2 at 63.0, and behind ElevenLabs' Eleven v4 at 70.0 and v3 Conversational at 66.8
➤ Pricing: Drama 3 is priced at $15/1M characters. Every model ranked above it on Provider Voice costs more: Gemini 3.8 Flash TTS at $16.5/1M, Qwen-Audio-3.1-TTS-Plus at $19.3/1M, Eleven v4 Turbo at $40/1M, Sonic 3.6 at $49/1M and Eleven v4 at $80/1M
➤ Open weights: released under the Fish Audio Community License.
See more details and listen to samples below ⬇️