Amir Asaleh

Medical Doctor

[Amir Asaleh @Doctechie1]

"Being bold and imaginative is really what's appropriate these days because there doesn't seem to be limits with the help we can get with AI"

Highly recommend watching this episode of Ground Truths with @pdhsu 🤓
https://t.co/zS47AQ4QHn

[Amir Asaleh @Doctechie1]

Huge congrats to my high school senior @oveisgharan on winning the IMU Abacus Medal! 🏆 Absolute brilliance. What a moment, what a life worth living! ✨

[Quanta Magazine @QuantaMagazine]

Shayan Oveis Gharan has won the Abacus Medal, one of the highest honors in theoretical computer science. Read our profile exploring how he used new mathematical tools to solve decades-old problems about route planning and random sampling: https://t.co/ohL2dgT4wx

[Amir Asaleh @Doctechie1]

🤯💯

[vitrupo @vitrupo]

David Sinclair says we’ll find out this year whether aging is reversible.

His lab reversed biological age in animals by 75% in six weeks. The FDA has cleared the first human trial.

Aging may be information loss.

Information can be restored.

[Amir Asaleh @Doctechie1]

Google Scholar names its most influential papers for 2025 https://t.co/KkzOeclHXg

[Amir Asaleh @Doctechie1]

Exactly

[Andrew Ng @AndrewYNg]

Some people today are discouraging others from learning programming on the grounds AI will automate it. This advice will be seen as some of the worst career advice ever given. I disagree with the Turing Award and Nobel prize winner who wrote, “It is far more likely that the programming occupation will become extinct [...] than that it will become all-powerful. More and more, computers will program themselves.”​ Statements discouraging people from learning to code are harmful!

In the 1960s, when programming moved from punchcards (where a programmer had to laboriously make holes in physical cards to write code character by character) to keyboards with terminals, programming became easier. And that made it a better time than before to begin programming. Yet it was in this era that Nobel laureate Herb Simon wrote the words quoted in the first paragraph. Today’s arguments not to learn to code continue to echo his comment.

As coding becomes easier, more people should code, not fewer!

Over the past few decades, as programming has moved from assembly language to higher-level languages like C, from desktop to cloud, from raw text editors to IDEs to AI assisted coding where sometimes one barely even looks at the generated code (which some coders recently started to call vibe coding), it is getting easier with each step.

I wrote previously that I see tech-savvy people coordinating AI tools to move toward being 10x professionals — individuals who have 10 times the impact of the average person in their field. I am increasingly convinced that the best way for many people to accomplish this is not to be just consumers of AI applications, but to learn enough coding to use AI-assisted coding tools effectively.

One question I’m asked most often is what someone should do who is worried about job displacement by AI. My answer is: Learn about AI and take control of it, because one of the most important skills in the future will be the ability to tell a computer exactly what you want, so it can do that for you. Coding (or getting AI to code for you) is a great way to do that.

When I was working on the course Generative AI for Everyone and needed to generate AI artwork for the background images, I worked with a collaborator who had studied art history and knew the language of art. He prompted Midjourney with terminology based on the historical style, palette, artist inspiration and so on — using the language of art — to get the result he wanted. I didn’t know this language, and my paltry attempts at prompting could not deliver as effective a result.

Similarly, scientists, analysts, marketers, recruiters, and people of a wide range of professions who understand the language of software through their knowledge of coding can tell an LLM or an AI-enabled IDE what they want much more precisely, and get much better results. As these tools are continuing to make coding easier, this is the best time yet to learn to code, to learn the language of software, and learn to make computers do exactly what you want them to do.

[Original text: https://t.co/HdI3Jb9HmF ]

[Amir Asaleh @Doctechie1]

😂💯

[Pat Azi @azi_pat]

geoffrey hinton: "train to be a plumber." greg brockman: "skilled trades like plumbers are in short supply and will be really difficult for ai to add value to." the godfather of ai and the president of openai independently arrived at the same career advice: learn to fix toilets.

[Amir Asaleh @Doctechie1]

🎯🎯

[Tesla Owners Silicon Valley @teslaownersSV]

Elon Musk on AI job replacement
“I'd say you're, you're pretty close to being able to replace half of all jobs, of- And you know that we're- white-collar jobs, that includes anything like education too.”

[Antonio Regalado @antonioregalado]

For those who are curious about unpublished scientific claims about rejuvenation from altos you can hear some of them here. year old presentation by co-founder Richard Klausner. https://t.co/oqLtpfRcaN

[Amir Asaleh @Doctechie1]

🎯

[Yahoo Finance @YahooFinance]

Nvidia CEO Jensen Huang says "AI is a five-layer cake" that's comprised of "energy, chips, infrastructure, models, and applications." 🎂

[Amir Asaleh @Doctechie1]

💯

[Startup Archive @StartupArchive_]

Jensen Huang: digital biology will be “one of the biggest revolutions ever”

“Where do I think the next amazing revolution is gong to come? And this is going to be flat out one of the biggest ones ever. There’s no question that digital biology is going to be it.”

Jensen continues:

“For the first time in human history, biology has the opportunity to be engineering, not science. When something becomes engineering, not science, it becomes less sporadic and exponentially improving. It can compound on the benefits of the previous years. And every researcher’s contributions compound on each other… We’re going to have incredible tools that bring the world of biology—which is very chaotic and constantly changing and diverse and complex—into the world of computer science. And that is going to be profound.”

He tells the student audience at Berkeley:

“If you happen to love this intersection, I think it’s going to be rich with opportunities. It’s going to be a giant industry.”

Video source: @BerkeleyHaas (2023)

[Amir Asaleh @Doctechie1]

And the same is true for decision making in whole life...

[Jon Erlichman @JonErlichman]

Steve Jobs on the healthy tension between evolution and revolution:

[Amir Asaleh @Doctechie1]

An absolute must-read after @davidasinclair 's Lifespan!
Thank you @EricTopol

[Eric Topol @EricTopol]

Excited to get a hold of my new book!
It's out in 1 month and can be pre-ordered.
https://t.co/KAuiN4Zbda

[Amir Asaleh @Doctechie1]

🎯

[Tsarathustra @tsarnick]

Jensen Huang says the next wave of AI is physical AI, which will require three computer systems to implement: AI, robot and Omniverse

[Amir Asaleh @Doctechie1]

Amazing! @geochurch

[TIME @TIME]

Scientists have bred woolly mice on their journey to bring back the mammoth. https://t.co/95Xlx37Qz8

[Amir Asaleh @Doctechie1]

Bro is walking in heaven...

[lada @ladanuzhna]

Each time I visit Boston, it's a cathartic experience. Snow. Freezing cold. Taking calls from empty MIT classrooms. People in small coffee shops on Kendall only talk about biology. The only gossip is about papers. All of the legendary biotech companies are located on the same block.

[Amir Asaleh @Doctechie1]

Still walking on the earth. Pushing for resilience and hard work.
So excited for what 2025 has in store.
Happy new year, folks!❤️

[Amir Asaleh @Doctechie1]

That restlessness — that tomorrow is more exciting than today — you have to have it permeate the organization.”

- Warren Buffett, 2013 at The Coca-Cola Company’s AGM

[Amir Asaleh @Doctechie1]

“I like to study failure. We want to see what has caused businesses to go bad, and the biggest thing that kills them is complacency. You want a restlessness, a feeling that somebody’s always after you, but you’re going to stay ahead of them,
1/2

[Amir Asaleh @Doctechie1]

Tiny batteries for powering cell-sized robots! Amazing work by @strano_group

https://t.co/QgMn777S0E

[Amir Asaleh @Doctechie1]

Amazing!

[Sakana AI @SakanaAILabs]

Introducing The AI Scientist: The world’s first AI system for automating scientific research and open-ended discovery!

https://t.co/jC7g5GPVsE

From ideation, writing code, running experiments and summarizing results, to writing entire papers and conducting peer-review, The AI Scientist opens a new era of AI-driven scientific research and accelerated discovery.

Here are 4 example Machine Learning research papers generated by The AI Scientist.

We published our report, The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery, and open-sourced our project!

Paper: https://t.co/lTQ8UenFHk
GitHub: https://t.co/Im53whVeAq

Our system leverages LLMs to propose and implement new research directions. Here, we first apply The AI Scientist to conduct Machine Learning research. Crucially, our system is capable of executing the entire ML research lifecycle: from inventing research ideas and experiments, writing code, to executing experiments on GPUs and gathering results. It can also write an entire scientific paper, explaining, visualizing and contextualizing the results.

Furthermore, while an LLM author writes entire research papers, another LLM reviewer critiques resulting manuscripts to provide feedback to improve the work, and also to select the most promising ideas to further develop in the next iteration cycle, leading to continual, open-ended discoveries, thus emulating the human scientific community. As a proof of concept, our system produced papers with novel contributions in ML research domains such language modeling, Diffusion and Grokking.

We (@_chris_lu_, @RobertTLange, @hardmaru) proudly collaborated with the @UniOfOxford (@j_foerst, @FLAIR_Ox) and @UBC (@cong_ml, @jeffclune) on this exciting project.