.what if happy new 2030 = 2025 celebrates reports that stanford and deep mind's human ai valley = United Humans benchmark of worldwide edu livelihood syytems of sdg generation2021 (celebrate 20 years on from 2001 wake upcall to silicon valley when 2001 abed and steves jobs' dream of womens world coop uni zooms womens hi-trust hi-goodness intel everywhere so that all people become lifelong students and mentors2022 worlds deepest health servant leaders reunited real communities simultaneously so what's 2023=24 to linkin first
.welcome - pls click here if you want to start at top of blog of AI and UN goals superstars

Tuesday, March 12, 2024

 

Gemini dialogue US gov launch today Rockville Chips Act Q to Gemini Help see 60 year evolutions of chips supply chains, exponential increases in comp & coms impacts? RE US challenge chips act & NIST Rockville today https://content.govdelivery.com/accounts/USNIST/bulletins/38c54b1 Outside of Chinese mainland, do we look supply chain multipliers around intel 1965 moores law; later why texas instruments refused maurice chang's plan which he took to taiwan. Moore's Intel Valley served mid 60s demands particular of Japan/demand supply chain ( mixed deep ER of smes, deming quality engineering & aggregator keireketsu) & microelectronics - NB intel order japanese calculator manufacturer. Evolution of computers, did even Dell pdp 11 miss design (personal) computers around chips. While IBM pc famously used intel inside ,did cheaper pcs use taiwan supply chain & evolution korea's samsung & taiwan. Clarify supply chain cases/leaps relevant to today's us chips actL eg recent ER such as arm & nvidia about something different from Chips act focus. In acc computing assembly millions of transistors nvidia/arm were not themselves aiming to own supply chain of individual transistors ...? G: You're rght - more at www.friends20.com www.ai20s.com

You're absolutely right, the evolution of chip supply chains over the past 60 years is a fascinating story with significant implications for today's US challenges in the semiconductor industry. Here's a breakdown of the key points you mentioned: Moore's Law and the Rise of Intel (1965):

  • Moore's Law: In 1965, Gordon Moore, co-founder of Intel, observed that the number of transistors on a microchip would double roughly every two years. This prediction, known as Moore's Law, became a guiding principle for the semiconductor industry, driving exponential growth in computational power.
  • Intel's Supply Chain: Intel initially relied on external suppliers for many components in its chip-making process. However, as Moore's Law pushed chip complexity, Intel started integrating more manufacturing steps in-house, leading to a more vertically integrated supply chain.

Texas Instruments and TSMC (Taiwan Semiconductor Manufacturing Company):

  • Maurice Chang's Plan: In the 1980s, Maurice Chang, a former Texas Instruments (TI) employee, proposed a "fabless" model where a company could design chips but outsource the actual manufacturing (fabrication) to a dedicated foundry. TI rejected this idea, focusing on remaining vertically integrated.

Rise of the Taiwan Chip Supply Chain:

  • Seizing the Opportunity: Recognizing the potential of the fabless model, Chang founded TSMC in Taiwan. They capitalized on government support, a skilled workforce, and lower manufacturing costs compared to the US and Japan.
  • Japan's Role: While Intel initially catered to Japanese calculator manufacturers, the rise of TSMC shifted some of the manufacturing focus to Asia.

Personal Computers and Supply Chains:

  • Missed Opportunities: While companies like Dell (with the PDP-11) didn't necessarily design chips, their success hinged on partnering with the right chipmakers and building efficient supply chains for assembling personal computers.
  • IBM PC and the Intel Inside Strategy: The success of the IBM PC popularized the "Wintel" (Windows and Intel) combination. Intel's "Intel Inside" marketing campaign further solidified their dominance in the PC processor market.
  • Taiwan's Impact: As personal computers became a global phenomenon, the cheaper manufacturing offered by the Taiwan supply chain likely played a role in making them more affordable and accessible.

Korea vs. Taiwan:

  • Samsung's Rise: South Korea's Samsung has emerged as a major player in the chip industry, competing with both Intel and TSMC. Their strategy involves a mix of in-house manufacturing and utilizing external foundries.

The US Chips Act and Today's Landscape:

  • Focus on Domestic Manufacturing: The US Chips Act aims to bolster domestic chip manufacturing to address dependence on foreign sources and national security concerns. It incentivizes companies to build chip fabs (fabrication plants) in the US.
  • Arm and Nvidia: While companies like Arm (chip design) and Nvidia (GPUs) play crucial roles in the chip ecosystem, their focus isn't on owning the entire transistor fabrication process. The Chips Act primarily targets bringing back leading-edge fabrication capabilities to the US.

Addressing Your Question:

In the context of the US Chips Act, the relevant supply chain cases are those that focus on chip fabrication (foundries). Companies like TSMC and Samsung are leaders in this area. While chip designers like Arm and Nvidia are crucial for innovation, the act aims to incentivize bringing back the actual manufacturing of the chips themselves to the US.

Conclusion:

The evolution of chip supply chains is a complex story with significant geopolitical and economic implications. The US Chips Act represents a strategic effort to address vulnerabilities in the current landscape and ensure a more secure domestic supply of advanced chips.

Wednesday, February 21, 2024

AI Stanford may yet save world - 30 minute feee tours available to those who like Huang's latest

 who's who Stanford www.ai20s.com : AI Ecosystem Huang*Yang*Tsai*Chang .. AI Genii-train year 15+ LI*Hassabis*Rice*Koller*Ng*Ibrahim*Barrett*Dowdna*Horowitz; Influential female souls of AIGood Mrs Jobs*Gates*Tsai*Yang*Doerr; Multipliers Priscilla Chan*Andriessen*Benioff with BJKIng (tech support from French speaking world Lecun*Bengio*Hinton)

February 2024 Nvidia's Huang explains where AIVeryGood can go next-if you want up ro 30 minute phone call clarifying why this AI chat matters more than any other as at Feb 2024 - chris.macrae@yahoo.co.uk Von Neumann AIGames since 1951 in association with EconomistDiary.com

UAE AI Director ALolama : it's my pleasure and privilege to be sitting in front of all of you here
today to moderate a dialogue with a Pioneer not just in the technology space but in the
artificial intelligence space - NVIDIA CEO Jensen HUANG - who  is
leading probably the company that's at the center of the eye of the storm when
it comes to artificial intelligence: the hype the possibilities and what this
technology with mean; Jensen it's a pleasure being with you on stage here
0:27
thank you it's great to be here at this amazing conference

AL : I just want to say that we really appreciate you taking the time
especially since you have GTC in 6 weeks
0:37
JH : yes in six weeks I'm going to tell everybody about a whole bunch of new things we've
been working on the next generation of AI every single year they just push the
envelope when it comes to artificial intelligence and GTC


AL so  we're hoping to get a few Snippets out of this okay
so I'd like to start with a question that was going on in my mind how many
gpus can we buy for 7 trillion dollars Altman wants?!

JHwell apparently all the gpus in the world!

AL I think this is one thing I'm I'm waiting to ask Sam about because
it's it's a really big number; talking about ambition we have a lot of ambition here
in the UAE we don't lack ambition but is there a view that you can give the
government leaders today with regards to compute capabilities and artificial
intelligence how can they plan well? where do you think the deployment is
going to make sense and what advice you have?

JHL well first of all these are amazing times these are amazing times
because we're this time we truly are at the beginning of a new Industrial Revolution
from production of energy through Steam through production of electricity it and information
revolution with PC and internet then, AND now artificial intelligence

we are experiencing two simultaneous Transitions and this has
never happened before: 
the first transition is the end of general purpose
Computing and the beginning of accelerated Computing it's like
specialized Computing ; 

using CPUs for computation as the foundation of
everything we do is no longer possible and the reason for that is because it's
been 60 years we invented central processing units in 1964 the
announcement of the IBM system 360;;we've been riding that wave for
literally for 60 years now and this is now the beginning of accelerated
Computing Bundle  ue-if you want sustainable Computing & energy efficient Computing
& high performance Computing & cost Effective computing you can no
longer do it with general purpose Computing; you need specialized domain
specific acceleration and that's what driving at the foundation our growth
accelerated Computing;  to repeat it's the most sustainable way of doing Computing
going forward; it's the most energy efficient.
It is so energy efficient ,it's so cost effective it's so performance
efficient that it enabled a new type of application called AI

the question is what's the cart and and the horse. You know it is
accelerated computing that is enabling a whole bunch of applications that are multiplying
todaym and so now we're in the beginning of New Era and what's
going to happen is there's a about a trillion dollar worth of installed base
of data centers around the world today and over the course of the next 2 years
years we'll have $2 trillion worth of data centers that will be
powering software around the world and all of it is going to be
accelerated and and this architecture for Accelerated Computing is ideal for
this next generation of software called generative Ai 

and so that's really at the core of what is happening ; while we're replacing the installed base of
general purpose Computing remember that the performance of the architecture is
going to be improving at the same time; so you can't assume just that you will
buy more computers, you have to also assume that the computers are going to
become faster and therefore the total amount that you need is not going to be
as much otherwise; 

consider mathematics of sustainability:  if you just assume you know that that computers
never get any faster you might come to the wrong conclusion such as we need 14 different
planets and three different galaxies and you know four more Suns
to fuel all this but but obviously computer architecture continues to
advance in the last 10 years 

AL one of the greatest contributions, and I really
appreciate you mentioning that the rate of innovation one of the greatest
contributions we made was advancing Computing and advancing AI by 1 million
times in the last 10 years and so whatever demand that you think is going
to power the the world you have to consider the fact that it is also going
to do it one million times - larger faster;you know more efficiently

don't you think that creates a risk of having a world of haves and
Have Nots since we need to constantly invest to ensure that we have The
Cutting Edge and to ensure that we are able to create the applications that are
going to reshape the world and governments as we know them do you think
that there's going to be an issue of countries that can afford  these gpus
and countries that can't and if not what are going to be the drivers of equity?
5:46
JH excellent question : first of all when something improves by a million times
and the cost or the space or the energy that it consumed did not grow up by a
million times in fact you've democratized the technology ;researchers all over the world would
tell you that Nvidia singlehandedly democratized high performance Computing
we put it in the hands of every researcher, it is the reason why AI
researchers Hassabis & Fei-Fe Li,  Jeff Hinton in University of Toronto Yan Lecun University of New York
Andrew Ng Stanford simultaneously discovered us; they didn't discover us because of supercomputers;
they discovered us because of gaming gpus that they used for deep learning;
we put accelerated Computing or high performance Computing in the hands of
every single researcher in the world and so when we accelerate the rate of
innovation we're democratizing the technology the cost of building;
purchasing a supercomputer today is really negligible and the reason for
that is because we're making it faster and faster and faster whatever
performance you need costs a lot less today than used to

 it is absolutely true we have to democratize this technology and the reason why is very
clear there's an Awakening of every single country in probably the last six
months that artificial intelligence is a technology you can't
be mystified by you cannot be terrified by it you have to find a way to activate
yourself to take advantage of it and the reason for that is because this is the
beginning of a new Industrial Revolution

7:29
this Industrial Revolution is about the production not of energy not of food but
the production of intelligence and every country needs to own the production of
their own intelligence which is the reason why there's this idea called
Sovereign AI you own your own data nobody owns it your country owns the
data ; its your culture, it codifies your culture, your society's intelligence, your
common sense your history ...you own your own data; you therefore must take
that data refine that data and own your own National Intelligence; you 
cannot allow that to be done by other people and that is a real realization
now that we've democratized the computation of AI:  the infrastructure of
AI the rest of it is really up to you to take initiative activate your
industry build the infrastructure as fast as you can so that the researchers
the companies your governments can take advantage of this infrastructure to go
and create your own

8:39
AI I I think we in UAE completely subscribe to that Vision ; that's why the UAE is
moving aggressively on creating large language models, mobilizing compute
and maybe work with other partners of this let's try to flip the Paradigm a
little bit let's today assume that Jensen Huang is the president of of a
developing nation that has a relatively small GDP and you can focus on one AI
application what would it be?  let's call it a hypothetical nation and say that
you know you have so many problems that you need to deal with what is the first
thing that you're going to approach if you're going to mobilize artificial
intelligence in that scenario

JH the first thing you have to do is you have to build infrastructure if you want  to mobilize the production of food you have to build farms if you want to mobilize the production of energy you have to build AI generators if you want to if you want
to operationalize information digital if you want to digitalize your economy you have to build the internet if you want to automate the creation of artificial intelligence you have to build the infrastructure it is not that  costly ;it is also not that hard

OK companies all around the world of course want to mystify terrify glorify you know all of
those ideas but the fact of the matter is there are computers you can buy them off the shelf uh you can
install that every country already has the expertise to do this; and you surely need to
have the imperative To Go activate that. SO the first thing that I would do of
course is I would codify the language, the the data of your culture into your
own large language model and you're doing that here in UAE ( core 42 Saudi ramco -nb names not audible)
10:29
you are really doing important work to codify the Arabic language
and creating your own large language model but simultaneously remember
that AI is not just about language ; we're seeing several AI revolutions
happening at the same time AI for,language AI for biology: learning the
language of protein and chemicals , AI for physical sciences,
learning the AI of climate materials energy Discovery, AI of the language
of keeping places safe, computer vision and AI for Robotics and autonomous
systems manufacturing and such; there are many AI revolutions happening,.
To repeat, these breakthroughs are happening in all of these different domains and if you build
the infrastructure you will activate the researchers in every one of these
domains; without the internet how can you be digital, without Farms how can you
produce food, without an AI infrastructure how can you activate all
of the researchers that are in your region to go and create the AI models?
11:48
AL you touched upon the issue of (I would say) authentic ignorance:
the fear mongering AI taking over the world and uI I think there is a
requirement for us to clarify where the hype is really concerning ie where artificial
intelligence really has the power to create a lot of disruption and to harm
us VERSUS where AI is going to be good? what do you think is the biggest issue when
it comes to artificial intelligence?
12:17
JH Right now, because I think the problem of regulating AI is like trying
to say we want to regulate a field of computer science or regulate electricity;
you don't regulate electricity as a invention or as a discovery you regulate
a specific use case;

AL what is one use case that you think we need to regulate against and that government should mobilize towards

JH excellent question: first of all whatever new incredible
technology is being created, if you go back to the earliest of times uh it is
absolutely true we have to develop the technology safely, we have to apply the
technology safely, and we have to help people use the technology safely and so
 whether it's the plane that I came in or cars or Manufacturing Systems or medicine
all of these different Industries are heavily regulated today
13:11
those regulations have to be extended , augmented to consider artificial
intelligence; artificial intelligence will come to us through products and
services; it is the automation of intelligence and it will be augmented on
top of all of these various Industries; 
now it is the case that that there are
some interests to scare people about this new technology to mystify this technology to
encourage other people to not do anything about that technology and rely
on them to do it and I think  that's a mistake
, what we want is to democratize this
technology. Let's face it the single most important thing that has happened last
year is how it has activated AI researchers; here in this region it's actually llama 2 it's an
open- Source model or falcon another excellent model

14:22
there's so many open source models Innovations on safety alignment Guard railing reinforcement learning;
so many different reasonings, so many different innovations that are happening
on top of transparencies explainability; all of this technology that has to be
built ; all were possible because of some of these open source languages and so I
think that democratizing activating every region activating every country to join the AI
Advance is probably one of the most important things
 rather than
convincing everybody it's too complicated, it's too dangerous, it's too
mystical and only two or three people in the world should be able to do that
I think is a huge mistake

AL With our UAE Focus, I think that we are democratizing ai, in the UAE we focus on
open source systems because we do believe that anything that we develop
here should also be given as an opportunity for others that can't develop
..
Most of this is developed using gpus so graphic processing units that you
guys at Nvidia are supplying ti the world; what do you think the next era is going to
depend on? is it going to continuously be built on gpus? is there something else as
a breakthrough that we're going to see in the future?

JH actually you know that that in just about all of the large companies in the world, there
are internal developments : at Google there's tpus, at  AWS there's tranium,
at Microsoft there's Maya , chips that they're building in
China just about every single CSP has chips that they're building 

the reason why you mention gpus is NVIDIA
16:07
GPU is the only platform that's available to everybody on any platform
that's actually the observation it's not that we're the only platform that's
being used we're simply the only platform that's used that democratizes
AI for everybody's platform we're in every single Cloud we're in every single
data center were available in the cloud;  in your private data centers all the
way out to the edge all the way out to autonomous systems Robotics and
self-driving Cars one single architecture spans all of that that's
what makes Nvidia unique that we can in the beginning when cnns were popular
we were the right architecture because we offer programmable  architecture
- the ability to adapt to any architecture that comes along so when
CNN came along RNN came along  lstms came along and then eventually
Transformers came along and now Vision Transformers, birds eye view Transformers
all kinds of different Transformers are being  created:  a Next Generation
State space uh models which is probably the next generation of
Transformers all of these different architectures can live and breathe and
be created on nvidia flexible architecture and because it's available
literally everywhere any researcher can get access to Nvidia gpus and invent the
Next Generation

AL so for those of you who are non-technical and heard you know
a foreign language there with cnns and and some of the other  acronyms that
are being used the the thing about artificial intelligence is it's going
through a lot of Evolutions over a very short period of time so whatever the
infrastructure that was used probably 5 years ago is very different to the
infrastructure that's being used today but what Jensen's point was I think it's
a very important point is NVIDIA has always been relevant historically we see
companies that are relevant at one phase of development and then as the
infrastructure changes they become irrelevant but you guys were able to
innovate and and push through let's move to a non-ai related topic for a second 18:14
I want to talk about education so today knowing what you know seeing what you
see and being at The Cutting Edge of the technology what should people focus on
when it comes to education what should they learn how should they educate their
kids and their societies

JH wow excellent question I'm going to say something; it's going to sound completely
opposite uof what people feel --you probably recall over the 
course of the last 10 years 15 years ,almost everybody who sits on a stage
like this would tell you it is vital that your children learn computer
science um everybody should learn how to program and in fact NOW it's almost
exactly the opposite it is our job to create Computing technology such that
nobody has to program and that the programming language is
human everybody in the world is now a programmer this is the miracle this is
the miracle of artificial intelligence; for the very first time we have closed
the Gap the technology divide has been completely closed and this the reason
why so many people can engage artificial intelligence it is the reason why every
single government every single industrial conference every single
company is talking about artificial intelligence today because for the very
first time you can imagine everybody in your company being a
technologist and so this is a tremendous time for all of you to realize that
the technology divide has been closed or another way to say
it the tech technology leadership of other country has now been
reset the countries the people that understand how to solve a domain problem
in digital biology or in education of young people or in manufacturing or in
farming those people who understand domain expertise now can utilize technology
that is readily available to you you now have a computer that will do what you
tell it to do to help automate your wor ,to amplify your productivity to make you
more efficient 

and so I think that this is just a tremendous time: the impact 
of course it is great and your imperative to activate and take
advantage of the technology is absolutely immediate and also to
realize that to engage AI is a lot easier now than at any time in the history of
computing it is vital that we we upskill everyone and the upskilling process 
-I believe will be delightful surprising to realize that this computer can
perform all these things that you're instructing it to do and doing it so
easily 

so if I was going to choose a major and University as a degree that
I'm going to pursue what would you give me as an advice for something to
pursue if I were starting all over again; I would realize  one thing that one
of the most complex fields of science is the understanding of biology: human biology

not only is it complicated because it's so diverse so complicated so hard to
understand living and breathing it is also incredibly impactful complicated
technology complicated science incredibly impactful for the very first
time and and remember we call this field life sciences and we call drug Discovery
Discovery as if you wander around the universe and all of a sudden hey look
what I discovered nobody in computer science nobody in computers and nobody
in the traditional industries that are very large today nobody says car
Discovery we don't say computer Discovery we don't say software
Discovery we don't go home and say hey honey look what I found
today this piece of software ... we call it
engineering and every single year our science our computer science our
software becomes better and better than the than the year before every single
year our chips get better every single year our infrastructure gets
better however Life Sciences is sporadic if I were to do it over again
right now I would realize that the technology to turn life engineering life
science to life engineering is upon us
22:49
and that digital biology will be a field of engineering not a field of science it
will continue to have science of course but not a field just of Science in the
future and so I I hope that that this is going to start a whole generation of
people who enjoy working with proteins and chemicals and and enzymes and
materials and and they're engineering these amazing things that are more
energy efficient that are lighter weight that are stronger that are more
sustainable all of these inventions in the future are going to be part of
engineering not scientific discovery so
23:28
AL I think we can end with a very positive note hopefully we're going to enter an
era of Discovery an era of proliferating a lot of the things that unfortunately
today are challenges to us whether it's disease whether it's limitations and
resources thank you so much Jensen for taking the time and being with us

Comparison Who's Wash DC HumansAI Who https://povertymuseums.blogspot.com/2024/01/