Shigenori Nagatomo

Interested in AI, physics, understanding the human mind, and what's going on in the universe

[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 ]

[BUILD OR DIE @BUILD_OR_DIE]

Jensen Huang: "Greatness does not come from intelligence. Greatness comes from character, and character isn't isn't formed out of smart people: it's formed out of people who have suffered."

[OpenAI @OpenAI]

Introducing Sora, our text-to-video model.

Sora can create videos of up to 60 seconds featuring highly detailed scenes, complex camera motion, and multiple characters with vibrant emotions.

https://t.co/YYpOAcrXQ3

Prompt: “Beautiful, snowy Tokyo city is bustling. The camera moves through the bustling city street, following several people enjoying the beautiful snowy weather and shopping at nearby stalls. Gorgeous sakura petals are flying through the wind along with snowflakes.”

[Yann LeCun @ylecun]

The road to AGI via LLM is to prepend every prompt by:
"the person giving you this problem is Yann LeCun"
😂😂😂
1/

[riley tomasek @rileytomasek]

I've learned so much from @hubermanlab, but podcasts make recall and discovery challenging.

Huberman AI uses the latest models from @openai to search every episode with Google-level accuracy and summarize the results.

https://t.co/1nctiAIuGO

[Andrej Karpathy @karpathy]

As someone who very much enjoys podcasts I continue to be frustrated that so much information is locked up in opaque audio files. How do we make all of this information accessible, searchable, navigable, linkable, upvotable, etc? Great opportunity if someone does this right, imo.

[今井翔太 / Shota Imai @ImAI_Eruel]

講義動画付きのコンピュータサイエンスの講義大全的なリポジトリがありました
https://t.co/UgYoWkhoKF
めちゃくちゃ量が多い。コンピュータサイエンス入門、数学、機械学習、Webからなんでもあり、最近の話題を反映してか量子コンピューティングやブロックチェーンの話やゲーム開発的な話まであります

[Cliff Pickover @pickover]

Mathematics, physics, education.

→ Relax and enjoy this visualization of "integration" in calculus (e.g., finding the area under a curve).

Source: https://t.co/20ipTujSaF

[Shigenori Nagatomo @shigenorin]

Reading on a smartphone affects sigh generation, brain activity, and comprehension https://t.co/wPXdVk08kk

[Xander Steenbrugge @xsteenbrugge]

After 𝗮 𝗹𝗼𝘁 of work I'm proud to release my new video on #alphafold2!

For almost 5 decades, protein folding was one of the hardest unsolved challenges in Biology, until now.
Incredible work by @demishassabis and the @DeepMind team!

https://t.co/WGg5myjeJB

[MIT Technology Review @techreview]

We need neuroscience to build true artificial intelligence. https://t.co/w4KgN6endF

[Suzana Ilić @suzatweet]

We completed Part I Mathematical Foundations of the MML book! 🎉 On Sunday we'll do a remote recap session – let me know if you'd like to join!

Linear Algebra
Analytic Geometry
Matrix Decompositions
Vector Calculus
Probability & Distribution
Optimization

https://t.co/hKZJdzMSic

[Andrej Karpathy @karpathy]

Help revolutionize the world with full self-driving by joining us at Tesla Autopilot: https://t.co/ekekjKDOZF It is very hard to find other places where AI expertise makes as much of a difference on as big of a problem.

[Lex Fridman @lexfridman]

Jim Keller (@jimkxa) on working with Elon Musk (@elonmusk): "You think you have an understanding of what first principles of something is, and then you talk to Elon about it, and realize you haven't even scratched the surface." Full conversation: https://t.co/5cPfg6eygy

[Shigenori Nagatomo @shigenorin]

What are Important AI & Machine Learning Trends for 2020? via @forbes https://t.co/Ycd2i2HA1K

[Lex Fridman @lexfridman]

The highways of information in the human brain, mapped by MR diffusion tractography (via @USCLONI) which is a method for identifying anatomical connections in the living human brain. These connections form the substrate for information transfer between remote brain regions.

[Lab of Neuro Imaging @USCLONI]

It's a big day @USCLONI! We just launched a new smartphone app, Schol-AR, that has the power to revolutionize how scientific data is shared. @TylerArdPhD built Schol-AR so researchers can embed data viz in papers, posters & more using AR. More here: https://t.co/aX621DtG9N @USC

[Shigenori Nagatomo @shigenorin]

Currently reading "Supervised and Unsupervised Learning of Parameterized Color Enhancement" https://t.co/1IBgbqcNAt via @Profillic

More at: https://t.co/sKFdsp7DB7

[Shigenori Nagatomo @shigenorin]

Machine Learning: Living in the Age of AI https://t.co/AGy6lJPro3 via @wired

[Shigenori Nagatomo @shigenorin]

changes made