Stupid fat hobbit

We're taking the hobbits to Isengard ...

[🏛 𝐒𝐭𝐞𝐯𝐞𝐧 🏛 @nonregemesse]

I just found out that Sir Patrick Stewart has died.

Here is a video he made on the advice he would give to his younger self.

RIP

[Tim Sweeney @TimSweeneyEpic]

This is awesome and hilarious as well!

[Stupid fat hobbit @StupidFat2026]

@thsottiaux Nice move Tibo!

[Tibo @thsottiaux]

Day 25/

We are doubling all usage limits for all Pro 100/200/500 tiers and Business Premium, effective today.

We heard your kind feedback and won’t be reducing usage limits for Pro 200, so your Work and Codex usage will stay the same. We’re also going to continue offering extended limits for dots for now, and usage of your dot will still continue to be separate from your default usage.

And we'll of course also keep shipping better models and other efficiency improvements that increase your effective usage over time.

[Stupid fat hobbit @StupidFat2026]

@Dare48910 @stepsenmccool @sparbuchfeinde Wer ich? Naja, wie ich sagte, im Endeffekt werden wir ALLE durch KI und Robotik ersetzt nur muss halt die dadurch geschaffene Produktivität allen zugute kommen und ob das klappt sei mal dahingestellt, ich möchte aber optimistisch sein.

[Stupid fat hobbit @StupidFat2026]

@Blaze2Bulls Ja ich kauf auch fast alles online, aber Douglas ist da echt entspannt ... zumindest ist das meine Erfahrung.

[Stupid fat hobbit @StupidFat2026]

@PikAssDE Ja aber das kann man doch nicht absehen sondern muss sich erst darauf einstellen, wenn das Kind wieder in den Brunnen gefallen ist.

[Stupid fat hobbit @StupidFat2026]

@notjuststone Not at all. She's obviously a psychopath that is best kept in a forensic psychiatry after jail. Someone having enjoyed this devilish thing is clearly better out of society.

[Elon Musk @elonmusk]

@battleangelviv Saving money for the distant future is pointless with the advent of super intelligent abundance

[Stupid fat hobbit @StupidFat2026]

@AliCologne Nix, ich geb Ihr noch nen 50 Euro Schein, damit sie richtig was kaufen kann die Woche und bezahle dann ihren Einkauf.

[Elon Musk @elonmusk]

If you look closely enough, breakthroughs in everything are accelerating exponentially.

An exponential always starts off looking small.

[Stupid fat hobbit @StupidFat2026]

@ifOnlyKantala @grok She does love carbs, doesn't she?

[Stupid fat hobbit @StupidFat2026]

@NB251299 @grok what was the outcome of this incident?

[Stupid fat hobbit @StupidFat2026]

@rajivasr @ecgrhythms @SergioPinski @syamkumarmd @KostekMilan @Frances98392343 @Ecgloverr @The_Nanashi_O @ecgandrhythmRoe Brugada?

[Derya Unutmaz, MD @DeryaTR_]

Why I believe AI / SI will unlock cures for every Cancer within the next five to ten years ears - PART 1:

For decades, cancer researchers have confronted a seemingly impossible problem: the biological complexity of cancer is so enormous that no individual scientist, research team, or even the entire scientific community can systematically explore all possible therapeutic solutions.

Consider what happens inside a single tumor. Thousands of genes, proteins, metabolites, and signaling pathways interact across millions or billions of cells. Then cancer cells constantly evolve, acquiring mutations, adapting to their environments, escaping immune surveillance, and developing resistance to treatments. Their behavior is further influenced by surrounding immune cells, blood vessels, fibroblasts, and the metabolic conditions within the tumor.
And every patient's cancer is different.

This creates an astronomical number of possible biological states and therapeutic interventions. Even when scientists identify a promising molecular target, they must determine whether interfering with it will actually kill the cancer, whether healthy tissues depend on the same mechanism, and whether the tumor will eventually escape.

Historically, we’ve approached this problem through relatively very slow cycles of hypothesis generation, experimentation, and clinical testing. We investigate a limited number of targets, screen a fraction of possible compounds, and spend years determining whether a treatment works.

Now imagine what happens when the intelligence available to solve these problems increases exponentially.

I believe the next five to ten years will bring superintelligence systems whose scientific reasoning, computational modeling, and experimental capabilities will vastly exceed those of today's best researchers put together!

The implications for cancer research will be profound. Here is the part 1 of how this can be achieved:

Virtual cells:
One of the most exciting developments will be the emergence of virtual cells, or computational models designed to predict how living cells behave and respond to interventions

Imagine an AI system that can represent a cancer cell's molecular machinery, including its genetic mutations, gene expression, protein interactions, metabolism, and signaling networks. Instead of testing one drug at a time, scientists could ask the model what would happen if they inhibited a particular protein, activated a specific immune pathway, edited a gene, or administered several treatments simultaneously.

Now extend that capability to millions of virtual cancer cells representing different tumor subpopulations, together with immune cells and healthy tissues.
We could potentially simulate how an entire tumor responds to treatment, how resistant populations emerge, and how different interventions affect normal cells!

This is the vision of increasingly comprehensive biological foundation models: AI systems trained on extensive molecular and experimental data that learn generalizable principles of cellular behavior.

The extraordinary opportunity is that such systems could eventually discover therapeutic mechanisms that we have never considered because we lack that computational capability. They might identify previously unrecognized combinations of molecular vulnerabilities, predict how to overcome resistance, and design interventions that exploit subtle differences between malignant and healthy cells.

Today's virtual-cell models are still very limited approximations of biology. But their predictive accuracy and scope will improve dramatically, and they will become powerful engines, accelerating precise therapeutic discoveries by magnitudes faster!

Part 2 will be about the digital twins. To be continued.

[Anthropic @AnthropicAI]

Over the past few months, Anthropic scientists have engaged in deep research partnerships with six organizations developing new medicines. We've also begun drug discovery efforts of our own.

In doing so, we’ve learned much more about how Claude can support the many stages of drug development.

In this blog post, we share some early results from these efforts, and describe how this work fits in with our wider ambitions in the life sciences.

https://t.co/EVbxkdDTgJ

[Stupid fat hobbit @StupidFat2026]

@IndependentEco "...after 5 long weeks." ... what a time to be alive

[Stupid fat hobbit @StupidFat2026]

@bridgemindai Do you have any guess when this is coming? I am on my 4th Claude Max 20x subscription...

[Stupid fat hobbit @StupidFat2026]

@WolleErz @Numm3rVi3r Helge G. ?