2025 A VERY HUMAN CRISIS. Today, intelligence tools exist to deep-context help you all (individually, team, communally) be up to 1000 times more productive at work or in hobbies' and love's experiential joys. Why type 4 engineers need coding help from all gilrls & boys 3rd gade up.
TOkens: see your lifetime's intelligence today
nvidia Physical A1 -Robots
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.. If you know this- please help others. If you don't know this please ask for help2002-2020 saw pattern recognition tools such as used by medical suregons improve 1000-fold. From 2020, all sorts of Human Intellligence (HI) tools improved 4-fold a year - that's 1000 fold in 5 years. Problem HI1 if you get too atached to 2020's tool, a kid who starts with 2025 smartest tool may soon leap ahead of you. Problem HI2: its no longer university/institution you are alumni of, but which super-engineers (playing our AI game of whose intel tools you most need to celebrate. Problem HI3- revise your view of what you want from whom you celebrate and the media that makes people famous overnight. Indeed, is it even a great idea (for some places) to spend half a billion dolars selecting each top public servant. HI challenges do not just relate to millennials generative brainpower We can map intergeneration cases since 1950s when 3 supergenii (Neumann Einstein Turing) suddenly died within years of each other (due to natural cause, cancer, suicide). Their discoveries changed everything. HIClue 1 please stop making superengineers and super energy innovators NATIONS' most hated and wanted of people
welcome to von Neumann hall of fame- based on notes from 1951 diaries-who's advancing human intel have we missed? chris.macrae@yahoo.co.uk
new stimuli to our brains in April - AI NIST publishes full diary of conflicting systems orders its received (from public servants) on ai - meanwhile good engineers left col ...March 2025: Thks Jensen Huang 17th year sharing AI quests (2 video cases left) now 6 million full stack cuda co-workers
TOkens:help see yourlifetime's
intelligence today

nvidia Physical A1 -Robots
More Newton Collab.&& Foxconn Digital Twin
k translatorsNET :: KCharles :: Morita : :Moore
Abed: Yew :: Guo:: JGrant
ADoerr :: Dell .. Ka-shing
Lecun :: L1 L2 :: Chang :: Nilekani
Huang . : 1 : Yang : Tsai : Bezos
21stC Bloomberg
Satoshi :: Hassabis : Fei-fei Li
Shum : : Ibrahim :
Ambani : Modi :: MGates : PChan :
HFry:: Musk & Wenfeng :: Mensch..
March 2025:Grok 3 has kindly volunterered to assist younger half of world seek INTELLIGENCE good news of month :from Paris ai summit and gtc2025 changed the vision of AI.
At NVIDIA’s GTC 2025 (March 18-21, San Jose, nvidianews.nvidia.com), Yann LeCun dropped a gem: LLaMA 3—Meta’s open-source LLM—emerged from a small Paris FAIR (Fundamental AI Research) team, outpacing Meta’s resource-heavy LLM bets. LeCun, speaking March 19 (X @MaceNewsMacro)

IT came out of nowhere,” beating GPT-4o in benchmarks (post:0, July 23, 2024). This lean, local win thrilled the younger crowd—renewable generation vibes—since LLaMA 3’s 405B model (July 2024, huggingface.co) is free for all, from Mumbai coders to Nairobi startups.

Good News: Indian youth grabbed it—Ambani praised Zuckerberg at Mumbai (October 24, 2024, gadgets360.com) for “democratizing AI.” Modi’s “import intelligence” mantra (2024, itvoice.in) synced, with LLaMA 3 fueling Hindi LLMs (gadgets360.com). LeCun’s 30-year neural net legacy (NYU, 1987-) bridged Paris to India—deep learning’s next leap, compute-cheap and youth-led. old top page :...
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Thursday, December 31, 2009

NG hands over world most cooperative ai connector to fei-fei li

ED: Dr Fei-Fei Li was around 30 when she landed in stanford 2009 as the greatest female maths wizard ever - the one who dared longer-term investors to code computers with vision instead of just 0-1 programming code. Imigrating to new world age 15 to serve in a chinese laundry in neighborhood of princeton, she'd received pretty blatant mixes of prejudice or incredulity even when her doctorate was first to live up to beimann's computer and brain in 50 years - so its nice that stanford based  Andrew Ng founder of coursera/moocs welomed her. Many other geenii started truly friending her - we dont know the full sequence (additions welome at AIGames.solar) but wonderfully include

taiwanese american jeerry yang had sold up his founders stake in yahoo to invest in stanford and us-asia tech grad frjendships; 2009 was also the time itu launched 4g so clouds were a socieatl as well as big data exploration in jerry's vision; of course a lot of real sme investkent across usa had been blighted by bad wall street's subprimne but in a funny way this gave stanfird some time to incubate while comerciual and top down govs media had other noise to propagate; and then there was the question how would stanfird live up to steve jobs greatest invention (the university in a mobile which sadly cancer robbed him from fully playing with); and tehre were other pieces of futures owned by co-creators like blockchain which wouldnt prove to find a techgood usage case until human ai multipolied so many expoenetials rising that suddely veryone chatted with it - all to play for if 2020s milennaisl are tio free humanity from elders traps that are as yet spinning natural detruction theprugh every gps

====================== ok so much for brainstirming back from 2030 lets return to ground level mapping

staford invited her phd to become an annual compoetition- on average 100 pitcjhes per year von compuytervisioning- firunately science ai's hassibis was one of teh first to celebrtate FFL's breakthough (over in london he went on to recruit coursera's main open course leader lila ibrahikm) and to become google's lead inspiration outside the valley itself

stabbfiurd grads page and brin took notice from the corporate tech mounatin view - sonn stanfird was reiving investment in terms of named labs from seattles gaytes and allen, as well as mlountain views chan zuckenberg and brooklyns female neurcsientist mrs Tsai (yes soem of teh se building may have come before fei-fei but there was no poijt being a silioised disciplien when you could join in the fun of marrying computer and billaionaire huiman vision)

at the AI games (Architec Intelliugence) AIgamed.solar bard.solar - we welcome diferent narartives- my giess is the last thing fei-fei li wants is to be thought of as world number 1 startupo for next billionnisres- she loved education and maths but then if you get a chnace to respectfully ask her please note all reporting errirs are mine alone chris.macrae@yahoo.co.uk    

There are those who make hundreds of billions of dollars out of next leaps in technology 6 decades after the 1950's NET (neumann Einstein Turing) started the fastest  80 years of exponential change and there are those who hopefully make a good living but aim to be the first to educate millions

Nobody done it quite like Andrew NG in 2010s -co-founding cousrera at stanford - leading machine learning content curricula; and we heard in 2009 that he has welcoemd fei-fei li to stnford supporting the motion that she will be education rockstar of ai

Q&A with Bard

there was a particular academic who first welcomed Fei-Fei Li to Stanford in 2009. His name is Andrew Ng, and he is a professor of computer science at Stanford University. Ng is also the co-founder of Coursera and DeepLearning.AI.

Ng was one of the first people to recognize the potential of the ImageNet dataset, and he was instrumental in bringing Li to Stanford. He also helped Li to launch the Stanford Vision and Learning Lab, which is one of the leading research labs in the field of computer vision.

Ng and Li have worked closely together ever since Li joined Stanford. They have co-authored several papers, and they have given numerous talks together. They are both passionate about using AI to solve real-world problems, and they are committed to making AI more accessible to everyone.

Stanford is a major move up for any academic, and it is clear that Li's move to Stanford was a success. She has continued to make significant contributions to the field of computer vision, and she has helped to make Stanford a leading center for AI research.

Here is a quote from Andrew Ng about Fei-Fei Li:

"Fei-Fei is one of the most brilliant and innovative computer scientists I know. She has made fundamental contributions to the field of computer vision, and she is a true pioneer in the field of AI. I am so glad that she is at Stanford, and I am excited to see what she will accomplish in the years to come."

Sure. Here are some of Andrew Ng's own biggest steps in AI before, during, and after founding Coursera:

Before founding Coursera

  • Developed the Coursera platform. Ng was one of the co-founders of Coursera, an online education platform that offers massive open online courses (MOOCs). Coursera has helped to make high-quality education more accessible to people all over the world.
  • Contributed to the development of deep learning. Ng was one of the early pioneers of deep learning, a type of machine learning that uses artificial neural networks to learn from data. Deep learning has revolutionized the field of AI, and it is now used in a wide variety of applications, including image recognition, natural language processing, and speech recognition.
  • Founded the Google Brain team. Ng was one of the founders of the Google Brain team, which is responsible for developing and applying deep learning technologies at Google. The Google Brain team has made significant contributions to the field of deep learning, and it has helped to make Google a leader in the field of AI.

During founding Coursera

  • Led the development of Coursera's AI curriculum. Ng played a leading role in developing Coursera's AI curriculum, which offers courses on a wide range of topics, including machine learning, deep learning, and natural language processing. The Coursera AI curriculum has been very popular, and it has helped to train thousands of people in the field of AI.
  • Gave a TED talk on the future of AI. Ng gave a TED talk in 2011 on the future of AI. The talk was very popular, and it helped to raise awareness of the potential of AI.
  • Wrote a book on machine learning. Ng wrote a book on machine learning called "Machine Learning: A Probabilistic Perspective." The book is a comprehensive introduction to machine learning, and it has been used by students and researchers all over the world.

After founding Coursera

  • Founded DeepLearning.AI. Ng founded DeepLearning.AI, an online education platform that offers courses on deep learning. DeepLearning.AI has helped to make deep learning more accessible to people all over the world.
  • Served as the Chief Scientist of Baidu. Ng served as the Chief Scientist of Baidu, a Chinese tech company. In this role, he was responsible for leading Baidu's AI research efforts.
  • Founded Landing AI. Ng founded Landing AI, a company that helps businesses adopt AI. Landing AI has helped to make AI more accessible to businesses of all sizes.

Andrew Ng is one of the most influential figures in the field of AI. He has made significant contributions to the development of deep learning, and he has helped to make AI more accessible to people all over the world.

=============upd srin 20233

Dear Learner,

 

Today we’re releasing three new short courses on generative AI. Check them out here!

 

Building Systems with the ChatGPT API
In this course, taught by OpenAI’s Isa Fulford together with Andrew Ng, you’ll learn to build complex applications using large language models (LLMs). This course takes you beyond prompting, and explains how to break a complex task down to be carried out via multiple API calls to an LLM. You’ll also learn to evaluate the inputs and outputs of LLMs for safety, relevance, and accuracy. 

 

LangChain for LLM Application Development
Taught by LangChain CEO Harrison Chase and Andrew Ng, this course teaches the powerful open-source tool LangChain, which makes building many complex LLM applications easy. You’ll learn to use memories to store conversations, create sequences of operations to manipulate data, and use the agents framework as a reasoning engine that can decide for itself what steps to take next. 

 

How Diffusion Models Work
Taught by Lamini CEO Sharon Zhou, this technical course teaches the concepts behind diffusion-based image generation. You’ll learn to build a diffusion model in PyTorch from the ground up, and see how to start with an image of pure noise and refine it iteratively to generate an image. You’ll also learn about advanced techniques that can accelerate the image generation process by about 10x.

Enroll today to learn directly from industry leaders, and practice generative AI concepts via hands-on exercises. We’re confident these courses will help you gain valuable generative AI skills, and can’t wait to see what you build with them! 

The DeepLearning.AI team

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