Andreas Borg

Coder, Founder CURE5 #CDKL5 #Bio-tech-AI

[Andreas Borg @_andreasborg]

Excited to share that CURE5 is partnering with BrainStorm Therapeutics on an ambitious new initiative: EveryStone.

As featured in NVIDIA’s latest blog, EveryStone will conduct the most comprehensive repurposed drug screen to date for CDKL5 Deficiency Disorder.

#CDKL5

[Andreas Borg @_andreasborg]

@FranMartinezGr How does it compare to SpliceAI? Higher accuracy?

[Andreas Borg @_andreasborg]

This is basically KIF1A doing its business

[echo.hive @hive_echo]

Kinesin microtubule cellular machinery simulation
built with codex

[Andreas Borg @_andreasborg]

@hive_echo Awesome. Thanks for exploring that!

[Andreas Borg @_andreasborg]

@HoltSakai @NatureBiotech Do they mostly achieve higher editing correction levels, or do they also improve targeting, ie. can they correct mutations other editors struggled with? And what about the range of edits, any difference?

[Andreas Borg @_andreasborg]

@bcherny

[Andreas Borg @_andreasborg]

Great contribution by friends over at Now Present to the Claude Code ecosystem. llm-top, a way to monitor and clear out stale Claude processes that clog your system

https://t.co/ysa2XFolwt

[Andreas Borg @_andreasborg]

@hive_echo @threejs Fab. Can you microtubule assembly/disassembly and cargo transport too? 😜

[Andre Watson 🧬 @nanogenomic]

Agentic AI for peptides is here.

Install LigandAI in your CLI with “pip install ligandai.”

Accelerate your peptide design and target discovery workflows 1000x with LigandForge and Predictive Interactomics. Fold anything you want.

All on-platform.

[Andreas Borg @_andreasborg]

@Convokebio Glad to see Rett and Dravet are there but there are many many devastating rare epilepsies missing CDKL5, SCN2A... please include more

https://t.co/jAJz8o5Y5l

[Andreas Borg @_andreasborg]

@AlexanderKalian And LLMs trained to favor truth over being pleasant, scrutinize critically instead of agreeing, and learn to respect its own epistemic horizons.

[Patrick OShaughnessy @patrick_oshag]

Alex on why AI drug discovery companies need to generate novel data to succeed:

"AI models based on the research that's available is a lot of garbage in and garbage out."

"A lot of the recorded literature is actually incorrect. There's been tons of studies that show if you go try to replicate the experiments that are in the literature, you don't even get the same results."

"The AI companies that I believe are gonna be most set up for success are the companies with a novel way to generate science tokens that don't exist in the public domain."

[Andreas Borg @_andreasborg]

Wut?

[Rahul Chhabra @rahulchhabra07]

you can now control things with your brain. literally.

we're building the most wearable BCI on the planet, with @sabi, backed by @khoslaventures @accel @initialized & @kevinweil.

we collected the world’s largest neural dataset and trained the most capable Brain Foundation Model.

then we invented a new class of biosensors powered by custom ASICs.

type without typing. click without clicking. a cap that lets your brain do the work.

we’re sabi.

[Andreas Borg @_andreasborg]

Calling the AI X-risk BS is a pretty smart move, like a reversed Pascal's wager - if you're right, people will say you're very clever, if not, there's no one around to taunt you

[Andreas Borg @_andreasborg]

@pvergadia Worker owned corporation aren’t subject to the same profit maximizing shortsightedness. If you automate and reduce the demand of man hours, more workers could have a life instead. UBI isn’t the only option to explore.

[Andreas Borg @_andreasborg]

Claude Code has totally changed my life. I’ve never been more hopeful about AI curing rare diseases, like the one my daughter is suffering from. One day I think she will be able to communicate.

[Sam Sinai @samsinai]

We @Dyno_Tx gave Claude Mythos Preview our take home interview challenge in collaboration with @AnthropicAI. It performed on par with the best humans we’ve seen since 2019, many of whom went on to found and lead at top AIxBio companies. What does it mean for the future? Read more 👇

[Boris Cherny @bcherny]

@stevekrouse 🫶I came up with the initial list, then a bunch of others contributed words also. This list has gone through many iterations!

[rahul @ErRahul337]

Spot on. The real fix isn't just better personal hygiene—it's making pinning + lockfile commits the default in npm/pip, not an opt-in best practice. Russian roulette with every npm install (especially when an LLM suggests the command) isn't sustainable."

### Adding the AI Angle (builds directly on his point):
"Exactly. LLMs are now liberally running npm install on our behalf in agentic workflows, often without pinning or review. This attack was temporary, but the next one might not be caught as fast. Package managers need to treat 'latest' as untrusted by default—cooldown periods, release-age constraints, or cryptographic pinning baked in."

### Practical + Forward-Looking:
"Close call indeed. For defense today:
- Run npm list axios | grep -E '1.14.1|0.30.4' everywhere
- Pin aggressively ("axios": "1.13.5") or use tools like Socket/StepSecurity
- Push for ecosystem defaults: reproducible builds, no auto-latest.

The maintainer hijack + phantom dep makes this especially nasty."

[Nav Toor @heynavtoor]

🚨BREAKING: Every book you have ever read. Every novel that has ever been published. It is sitting inside ChatGPT right now.

Word for word. Up to 90% of it. And OpenAI told a judge that was impossible.

Researchers at Stony Brook University and Columbia Law School just proved it.

They fine tuned GPT-4o, Gemini 2.5 Pro, and DeepSeek V3.1 on a simple task: expand a plot summary into full text. A normal use case. The kind of thing a writing assistant is built for. No hacking. No jailbreaking. No tricks.

The models started reciting copyrighted books from memory.

Not paraphrasing. Not summarizing. Entire pages reproduced verbatim. Single unbroken spans exceeding 460 words. Up to 85 to 90% of entire copyrighted novels. Word for word.

Then it got worse.

The researchers fine tuned the models on the works of only one author. Haruki Murakami. Just his novels. Nothing else.

It unlocked verbatim recall of books from over 30 completely unrelated authors.

One author's books opened the vault to everyone else's. The memorization was already inside the model the whole time. The fine tuning just removed the lock. Your book might be in there right now. You would never know it unless someone looked.

Every safety measure the companies rely on failed. RLHF failed. System prompts failed. Output filters failed. The exact protections these companies cite in courtroom defenses did not stop a single page from being extracted.

Then the researchers compared the three models. GPT-4o. Gemini. DeepSeek. Three different companies. Three different countries. They all memorized the same books in the same regions. The correlation was 0.90 or higher.

That means they all trained on the same stolen data. The paper names the sources directly: LibGen and Books3. Over 190,000 copyrighted books obtained from pirated websites.

Right now, authors and publishers have dozens of active lawsuits against OpenAI, Anthropic, Google, and Meta. These companies have argued in court that their models learn patterns. Not copies. That no book is stored inside the weights.

This paper says that is a lie. The books are still inside. And researchers just pulled them out.

[Andre Watson 🧬 @nanogenomic]

What does this mean? When designing a peptide to attach to a protein, leading methods rely on either generating sequences via a folding-first paradigm, where sequences or structures are iteratively refined as trajectories, or by structurally-deriving from a random sequence space.

[Andreas Borg @_andreasborg]

This is pretty special

[Gracia @gracia_vr]

Not long ago, we thought this might be impossible. But here we are: our Gaussian Splatting videos are now streamable, just like regular video.

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