Zeno

lupo è il mio secondo nome nulla lupo-related

[🚨 AI News | TestingCatalog @testingcatalog]

TypeSafe AI has introduced its first model named Jev - a small and customizable System One decision model.

Not being an LLM, Jev can’t reason or write explanations; it generates a fast judgment with calibrated probabilities and a confidence score.

Anything heavier gets split into separate questions and recombined in code.

TypeSafe reports a response time of approximately 150ms per call, at around 100x lower cost and faster responses than LLMs, with pricing at $42 per billion input tokens and free output.

[Casual Geopolitics @Adamemedia]

This isn’t a joke btw.

This is actually the U.S. economy.

This scam is going to come crashing down. Soon.

[Massimo @Rainmaker1973]

Visualizing bird sounds in 2D and 3D

[Klaas @forgebitz]

200k-mrr-startup-plz. md

[Wall Street Mav @WallStreetMav]

Zelensky demands ceasefire between Trump and Elon.

[† lucia scarlet 🩸 @luciascarlet]

the brightness slider is just made-up nonsense

[Karen McGee @karenmotherof2]

Shooter must’ve been Bronny James the way he went 1/8

[Zeno @zenolupo]

so this is how they do ear piercings in Pennsylvania

[Min Choi @minchoi]

It's only been a week since Gen-3 Alpha became available to public.

And you can't believe these are AI

10 wild examples:

[Elon Musk @elonmusk]

This should be a requirement. If Argentina can do it, so can America!

[proper @ProperPrompter]

Claude 3.5 Sonnet is not like the other LLMs 💁‍♀️

11 impressive demos of the new model:

[Massimo @Rainmaker1973]

Cognify, the prison of the future: a concept by Hashem Al-Ghaili

[🎞️ hashem.alghaili]
https://t.co/7iritCrXAz

[Min Choi @minchoi]

Claude 3.5 Sonnet + Artifacts changed the LLM game.

People are getting creative with wild use cases that were harder with GPT-4o. Is this the new AI king?

10 examples:

[Min Choi @minchoi]

AI brings memes to life.

Luma AI Dream Machine as Meme Machine 😂

10 wild examples:

1. Kabosu! @blizaine

[Epoch AI @EpochAIResearch]

1/ How quickly are state-of-the-art AI models growing?

The amount of compute used in AI training is a critical driver of progress in AI. Our analysis of over 300 machine learning systems reveals that the amount of compute used in training is consistently being scaled up at 4-5x/year.

Highlights in thread 🧵

[Min Choi @minchoi]

Google DeepMind team dropped more wild AI Agent videos.

3 examples:

1. Identify famous face and facts from drawings

[Elon Musk @elonmusk]

You really feel that bass

[Zeno @zenolupo]

1st Neuralink Patient’s Staggering Update https://t.co/bqSb1oOIFe via @YouTube

[Robert Scoble @Scobleizer]

Soon you will be able to build anything you can dream up. Or sketch out.

[Min Choi @minchoi]

5. Creates voice script to communicate h/t @skirano
https://t.co/mMASkgmvRe