Iñaki Fernández

[Iñaki Fernández @IFernandez___]

Estoy muy orgulloso de contarles que un proyecto en el que trabajé un largo rato, hoy apareció como un top project en “The Information”. Fuimos comparados con perplexity😍

https://t.co/meUMdhnegs

[Iñaki Fernández @IFernandez___]

Es increíble lo que este mundial me ha acercado a mis cuates ❤️‍🩹

[Iñaki Fernández @IFernandez___]

@h1sort Dale lo armamos

[Iñaki Fernández @IFernandez___]

@h1sort Que tal Devin?

[Harvey @harvey]

Would Harvey Specter use Harvey?

@GabrielMacht had to ask.

[BridgeMind @bridgemindai]

FABLE 5 CAME BACK NERFED.

We re-ran the July 1st version of Claude Fable 5 on BridgeBench.

The results are brutal:

Debugging: 86.2 → 25.9
Refactoring: 73.6 → 38.4
Hallucination: 75.9 → 61.7

The new guardrails are kicking in on way too many tasks and falling back to Opus 4.8.

This is not the model that got banned.

Anthropic owes everyone an explanation.

[Rob Hallam @robj3d3]

Excuse me sir, I have work to do.

[GREG ISENBERG @gregisenberg]

18 days without Fable felt like a decade. welcome home king. excited to see people go build their wildest dreams with it again.

never leave us again lol

[Iñaki Fernández @IFernandez___]

Fable 5 mañana, Mexico ganó hoy y novia guapa. Life is good 🚀

[Anthropic @AnthropicAI]

Claude Fable 5 will be available again globally tomorrow.

After a series of productive conversations with the US government, we're redeploying the model with a new set of classifiers to target and block more cybersecurity tasks. In the near term, some routine tasks like coding and debugging will fall back to Opus 4.8. We’ll continue to refine these classifiers over the coming weeks to reduce false positives and better distinguish genuine misuse from legitimate requests.

We’ve also begun drafting a consensus framework—with Amazon, Microsoft, Google, and other Glasswing partners—for assessing the severity of AI jailbreaks and how AI developers should respond to them. We invite other industry partners and model providers to join us in this effort.

Finally, we’re scaling up our collaboration with the US government on model testing and safeguards. This will include pre-release access to models and safeguards for evaluation, information sharing on jailbreaks and misuse, and dedicated resources for joint research.

Thank you to our users for your patience, and to our partners across the government, industry, and the research community who worked alongside us to make Fable 5 available again.

Read our full blog: https://t.co/VHyum831ri

[Polymarket Money @PolymarketMoney]

BREAKING: Anthropic reportedly renegotiated part of its $AMZN deal to price Claude usage by tokens instead of compute hours starting next year.

[Polymarket @Polymarket]

JUST IN: Meta unveils Brain2Qwerty v2, a non-invasive brain-to-text system that can turn raw brain signals into full sentences in real time.

[Raj Dabre @prajdabre]

This is cool!

Mark, I Owe You an Apology. I Wasn't Really Familiar With Your Game.

[AI at Meta @AIatMeta]

We’re sharing the next major milestone in our non-invasive brain-to-text decoder research: Brain2Qwerty v2.

Building on v1, which was published today in @Nature, Brain2Qwerty v2 is the highest-performing end-to-end pipeline capable of real-time sentence decoding from raw brain signals. It advances beyond character-level performance to decoding words and semantics, enabling accuracy for overall communication.

We believe this research has the potential to make a real difference for the millions of people who suffer from brain lesions or disorders that prevent them from communicating.

🧵👇

[elvis @omarsar0]

If you use LLM-as-judge, this one is worth reading.

(bookmark it)

It's actually one of the most effective ways to use LLM-as-a-Judge for evals.

Holistic judge scores hide both their reasoning and their ceiling effects.

BINEVAL decomposes each evaluation criterion into atomic yes-or-no questions, answers each independently per output, then aggregates the verdicts into calibrated multi-dimensional scores.

Every question-level verdict is inspectable, so you can diagnose exactly why an output scored low, and the same verdicts feed straight back as targeted prompt-improvement signal.

Across SummEval, Topical-Chat, and QAGS, it matches or beats UniEval and G-Eval, training-free, with especially strong results on factual consistency.

Paper: https://t.co/oar6BZcasm

Learn to build effective AI agents in our academy: https://t.co/1e8RZKs4uX

[Roger @rdd147]

Bank of Canada, Bank of International Settlement, and European Central Bank now all warning international insurers and pensions not to purchase US data center debt as the US is likely headed into financial catastrophe on defaults. Happy to see $BX is already willing and ready to dump every one of their empty data centers back to pensions in default.

$ORCL $SOXX $DRAM

[Martinalgui @MartinoliCuri]

Como se sintió ver 72 partidos de fase de grupos en 17 días:

[Aryan @aryanlabde]

Hot take:

vibe coding only works well if you already know how to code.

[Mikhail Parakhin @MParakhin]

Not as relevant now :-(: I had an opportunity to deeply test both Fable 5 and GPT-5.6 Max. 5.6 is clearly better than Opus 4.8 at everything (slightly faster, too, though that depends on the load). Vis-a-vie Fable, it is clearly worse on coding, but better on agentic workloads. I had Fable write code, 5.6 run experiments - dreamy…