Differentiation by „oh, you‘re also using loops and agents“ is like rating restaurants by the oven they use…
.@OpenRouter co-founder Alex Atallah on the "everyone is building the same thing" take:
"This reminds me of this tweet I saw... Everybody's building an agent loop with notifications, third-party connectors, context management, memory, sandboxes, agentic web search, an always-on agent on top."
"This product is showing up everywhere. It is showing up everywhere, but these are just the new table-stakes primitives."
"A 2005 version of that tweet would be: 'Oh, everybody's building the same thing. A database, a users table, a sign-in page, a sign-up page, a profile page, a logout page. Everything's the same.'"
"There's like a lot of differentiation really. There's table-stakes needs for AI just like there's table-stakes needs for the web."
@alexatallah @amasad
Opus 5.5 has an amazing way to communicate. Feels so good after the Opus 5 communication style. Well done @claudeai
Spending my Sunday playing with @trylatitude and love it! #promptengineer
Alex Jacobi retweeted
People have too inflated sense of what it means to "ask an AI" about something. The AI are language models trained basically by imitation on data from human labelers. Instead of the mysticism of "asking an AI", think of it more as "asking the average data labeler" on the internet.
Few caveats apply because e.g. in many domains (e.g. code, math, creative writing) the companies hire skilled data labelers (so think of it as asking them instead), and this is not 100% true when reinforcement learning is involved, though I have an earlier rant on how RLHF is just barely RL, and "actual RL" is still too early and/or constrained to domains that offer easy reward functions (math etc.).
But roughly speaking (and today), you're not asking some magical AI. You're asking a human data labeler. Whose average essence was lossily distilled into statistical token tumblers that are LLMs. This can still be super useful ofc ourse. Post triggered by someone suggesting we ask an AI how to run the government etc. TLDR you're not asking an AI, you're asking some mashup spirit of its average data labeler.
1/ 😎 Meta's neuestes AI-Modell ist so leistungsfähig wie die größten Modelle von OpenAI und Anthropic. Es ist Open Source und modifizierbar. Damit wird es möglich, viele spezialisierte Versionen zu erstellen, die in bestimmten Bereichen herausragend sind.
3/ 🔒 Ein spezielles, auf eine Marke abgestimmtes AI-Modell kann so immer besser darin werden, genau diese Marke zu verstehen, ohne dass die "Secret Sauce" außerhalb der Firma landet. Das Modell kann – Kleingeld vorausgesetzt – komplett InHouse betrieben werden. Ein GameChanger!
4/ 🏭 Aber: Ohne die nötige Infrastruktur wird das wohl kaum funktionieren. @GeorgRunge, hast du Einblicke, unter welchen Bedingungen das möglich ist?
Warum ich glaube, dass kleine KI Modelle wie PHI-1 von Microsoft die eigentliche Revolution sind: withloveanddata.com/p/kleine…
5/5: Habt ihr diese Methode schon mal ausprobiert? Teilt eure Erfahrungen! #AIAnwendung #ChatGPT
Alex Jacobi retweeted
What are prime applications of LLMs right now?
Tasks that are:
* Highly repetitive
* Have tons of text
* High value documents (ex: legal docs)
* High latency is ok (ex: you're emailing a human and can afford a few seconds)
Ich habe mir mal Gedanken gemacht, wie #ChatGPT mir beim Lernen helfen kann. Herausgekommen ist ein Spaced Repition Learning Bot :) withloveanddata.substack.com…
Google hat ein umfangreiches kostenloses E-Learning zum Thema generative AI veröffentlicht: cloudskillsboost.google/jour…






