Stanford just released a 386-page report on the state of AI
twitter.com
twitter.com
https://aiindex.stanford.edu/report/
Honestly though a quick skim of those bullet points in the Twitter thread and looking at the length of it (nearly 400 pages) I am sceptical it's not a lot of corporatese for execs.
Ps. already submitted here:
Checkout sitegpt as well if you want to create a query bot for your website.
The Artificial Intelligence Index Report 2023 provides insights into the current state of AI research, development, and adoption. Key findings and implications from the report include:
1. Research and Development: The United States and China lead in cross-country collaborations in AI publications, with the number of collaborations increasing four times since 2010. China has also overtaken the European Union and the United Kingdom in AI conference publications, producing 26.2% of the world's share in 2021.
2. Technical Performance: AI models have become more advanced, with the release of text-to-image models like DALL-E 2 and Stable Diffusion, text-to-video systems like Make-A-Video, and chatbots like ChatGPT. AI systems are increasing in complexity due to advancements in hardware, data availability, and larger model sizes.
3. Technical AI Ethics: In 2022, new ethics benchmarks and diagnostic metrics were introduced to address concerns about AI fairness, bias, and transparency. However, challenges remain in steering AI models to avoid harmful outcomes.
4. The Economy: AI hiring has grown in various countries, with Hong Kong experiencing the highest growth in 2022. Private investment in AI decreased for the first time in a decade, but AI remains a topic of interest for policymakers and industry leaders.
5. Education: The United States leads in AI-related postsecondary education, with a significant number of AI courses and programs offered at universities.
6. Policy and Governance: AI-related policymaking has increased, with the United States, Spain, and the Philippines leading in AI-related laws. Legal cases involving AI highlight the challenges and complexities of AI in the courts.
7. Public Perception: Men are more likely than women to report that AI products and services make their lives easier and trust companies that use AI. Surveyed Americans are most excited about AI's potential to make life and society better (31%) and save time and increase efficiency (13%).
8. AI Skills: The top AI skills include machine learning, natural language processing, data structures, computer vision, image processing, deep learning, TensorFlow, Pandas (software), and OpenCV.
[0]: https://kagi.com/summarizer/index.html [1]: https://kagi.com/summarizer/index.html?url=https%3A%2F%2Faii...
“the number of AI incidents and controversies has increased 26 times since 2012”
Ok but how many “incidents,” also detectably fake deepfakes and call-monitoring inmates are top examples of misuse? Naive.
“BLOOM’s training run emitted 25 times more carbon than a single air traveler on a one-way trip from New York to San Francisco”
What does this mean? That sounds like a very small amount to me but the conclusion is that’s a huge environmental impact. No, I read, for the carbon cost of decommissioning one old jet, we can have a new LLM.
Honestly seems like a good tradeoff.
This is roughly a 400 mile car trip, or about a year of breathing.
What you breathe out is mostly what you eat, and most of the carbon there is part of a continuous carbon cycle. A part of it comes from fossil fuels, mainly transport and energy to power the Haber Bosch (the source of most of (organic) hydrogen in your body).
LLM training process consumes practically only energy. As such, it could very easily be replaced by carbon-neutral sources (nuclear, solar).
All of the CO2 of a airplane flight comes from fossil fuels, and there is not viable technology to replace that yet.
Less than the cost to send the SF Giants to play the NY Yankees then?
I wonder how many SF to NY carbon units Stanford expends each year to send their various sports teams out to do important work?
This game is fun!
They made it clear they weren't joking, nor exaggerating. I have no idea how things got this way, nor why. Must be some kind of filter?
Forcing things onto a PPT forces clarity due to the form factor, not unlike a twitter thread.
Pentium (technically 586), released in 1993, is what I think of when I think of CPUs in the 90s. “n”86 has the 1980s association.
Generational divide, here.
It took off and spawned its own line, the 80168, 80286, etc. Eventually, the 80 was dropped and they became known as the 286, 386, 486. Even the Pentium processor was really a brand name for the 586.
Every Core i7 is an x86.
Your question makes me feel old :)
the only persons that did pointed it out is my best friend and his sister which for almost a decade my beloved wife
The Artificial Intelligence Index Report 2023 provides insights into the current state of AI research, development, and adoption. Key findings and implications from the report include:
1. Research and Development: The United States and China lead in cross-country collaborations in AI publications, with the number of collaborations increasing four times since 2010. China has also overtaken the European Union and the United Kingdom in AI conference publications, producing 26.2% of the world's share in 2021.
2. Technical Performance: AI models have become more advanced, with the release of text-to-image models like DALL-E 2 and Stable Diffusion, text-to-video systems like Make-A-Video, and chatbots like ChatGPT. AI systems are increasing in complexity due to advancements in hardware, data availability, and the performance of larger models.
3. Technical AI Ethics: In 2022, new ethics benchmarks and diagnostic metrics were introduced to address concerns about AI fairness, bias, and transparency. However, challenges remain in steering AI models to avoid harmful outcomes, such as toxicity, bias, and privacy violations.
4. Economy: AI hiring has grown in various countries, with Hong Kong experiencing the highest growth in 2022. Private investment in AI decreased for the first time in a decade, but AI remains a topic of interest for policymakers and industry leaders.
5. Education: The United States leads in AI-related postsecondary education, with a significant number of AI courses and programs offered at universities.
6. Policy and Governance: AI-related policymaking has increased, with the United States, Spain, and the Philippines passing the most AI-related laws in 2022. Legal cases involving AI highlight the challenges and complexities of AI in the courts.
7. Public Perception: Men are more likely than women to report that AI products and services make their lives easier and trust companies that use AI. Surveyed Americans are most excited about AI's potential to make life and society better (31%) and save time and increase efficiency (13%).
8. AI Talent: The top skills in the AI skill grouping include machine learning, natural language processing, data structures, computer vision, and deep learning, among others.
I don't believe AI output. My eyes glaze over and I scroll past it. Anything that looks AI formatted is branded with disbelief and a cognizant awareness that it produces unverifiable shades-of-grey.
Are we really going to live in a world where a blackbox program that does not produce meaningfully deterministic results and cannot be examined, is regarded as a source of truth?
If AI takes in a poisoned database and spreads it, who would know? The AI leaving out vital information is just as dangerous, though we are used-to that problem.
And that's before we even hit the accuracy of it's word predictions..
I don't understand why people are keen on 'being friends' with the grim reaper parrot.
"In 2022, there were 32 significant industry-produced machine learning models compared to just three produced by academia."
It seems frustrating to work in one of these top academic AI departments, with incredibly smart people, but with so much of the cutting edge work out of reach due to both the cost and the difficulty of running large scale infrastructure.
Experiment: What does ChatGPT produce when you ask it for a 300-plus-page report? Is it better or worse than the average human-written report of similar size?
I gather that with the current architecture it becomes exponentially more difficult to grow the window, but I'm not sure if that's what a computer scientist would call "exponential" or if it was the common colloquial usage that calls x^2 "exponential growth"; would actually be interested if anyone could clarify that. With the current expense though, any of the common complexity classes beyond O(n log n) isn't very feasible at the moment though.
Then there's this https://hazyresearch.stanford.edu/blog/2023-03-27-long-learn...
I don't think a 300 page context window is too far away
It’s actually more like working with a junior copy editor that you have to constantly correct, so you keep wondering what you’re even paying them for. But at $20 a month it’s worth it for that.
OP shouldn't have changed the report's title, or if this is the original title by some miracle, they should have changed it or posted a comment about why it's interesting. Presumably they did read at least part of it and have a reason for submitting it. As it is, the submission is entirely useless beyond pointing out that a certain URL exists.
01 Industry now leads academia in releasing significant machine learning models. 02 Traditional benchmarks are showing performance saturation, but new benchmarks are emerging. 03 AI has both positive and negative environmental impacts. 04 AI is accelerating scientific progress in various fields. 05 Incidents concerning AI misuse are rapidly rising. 06 Demand for AI-related skills is increasing across most American industrial sectors. 07 For the first time in a decade, year-over-year private investment in AI decreased in 2022. 08 While AI adoption by companies has plateaued, those that have adopted AI are experiencing cost and revenue benefits. 09 Policymaker interest in AI is growing, with more AI-related bills being passed into law. 10 Chinese citizens have the most positive view of AI products and services, while Americans are more skeptical.
Two different summaries -I can't point them currently but one of them chatGPT, one of them a credible software- created by two distinct models. While it's not scientifically accurate to claim they are significantly different, there are noticeable differences between them. I'd like to use ChatGPT to compare these summaries, as I believe its contextualization capabilities could help clarify the situation. However, there are people who have strong opinions against using ChatGPT, and they criticize each other for doing so. This resistance is causing me frustration and holding me back from pursuing the comparison, which is a pain point for me.
Is there a cultural reason for this?
It's more accurate to say that neural networks succeeded against the research darlings of the time despite being relatively ignored for decades.
More likely they are just throwing money around in an attempt to make the physical embodiment of the Middle East's oil-fueled, centuries-long democratic backslide look modern and progressive. MBS loves to chuck money at flashy tech (and also Fox News).
[0] Roco's Basilisk is just Pascal's Wager with a computer program that doesn't exist yet.
[1] As interpreted by the most intolerant Wahhabist
On the other hand, Arabs were extremely good at racial name calling (calling Persians Ajami, and calling chess evil and shit).
Take note the Islam SE community mostly comes from Stack Overflow and is somewhat biased towards tech. But it was a decent discussion with some solid citations.
tldr: Imitation of humans and other living creatures is not okay, but nothing wrong with imitation of intelligence.
This probably wasn't that true because obviously AI & robotics research is booming in the US.
But I think the data hints that consumer demand for AI and AGI might be significantly higher in China, etc. There was also the recent controversy around Midjourney banning Xi Jinping images lately, which suggests that they're eyeing the Chinese consumer market.
I also had this impression, especially after seeing demos of ASIMO. Looking back, ASIMO was always just a demo, Germany is a strong player in industrial robots, and Boston Dynamics is doing some very impressive demos. I have no idea who is/was actually ahead.
There must be a word for that?
There's been multiple AI winters, and it would be wise not to sweep them under the rug.
No one wants to read a 386 page report.
Any links for a version we could ask questions to?
You don't have to. The bulk of the report homepage is the top ten takeaways of the work in bite-size format. The body of the report is (or at least should be) the evidence that supports these statements. A good conclusion should always be supported by evidence.
This is the Tweet author's comment on a graph that shows the number of AI companies in different countries, rendered as a bar chart. The comment is a little cryptic -why would the number of AI companies in a country advise where you should start an AI company?
So I figured I'd try to understand the comment by engaging in a bit of arbitrary, ad-hoc math.
US: 542
Everyone else: 160 + 99 + 73 + 57 + 47 + 44 + 41 + 36 + 32 + 26 + 23 + 22 + 12 + 12 = 684
So I guess the logic was that, "you should be in the US if you're starting an AI company" because that's where you can expect the least competition.
That sounds like solid advice!
In terms of competition, evidently it’s working out relatively well in the USA as there are enough people there to support nearly half the AI companies on earth. It appears to be a very fertile bed for growth in this sector.
Further, most products will likely wind up online; there will not be much need for localized competition advantage outside of securing a team. The competition stage is largely a global market, online. You’re best forming your company where you can hire people and collaborate with other people in your sector. That’s ideally in the USA, so far.
That being said, there are actual factors for which the US might indeed plausibly be the best location choice specifically for most AI companies in the current hype context. For example funding:
* while there is also some proportion of actually promising sustainable business models based on AI, the fact is that a very large proportion of AI companies are surfing on a hype/bubble and have somewhat of an exit strategy (e.g. being bought by some bigger player) but not a business model that would otherwise sustainably stand on its own feet.
* the US is arguably indeed the best location for most high-risk ventures in need of big funding… including and especially so for hype/bubble surfers. Nowhere else can you find that much early investment money with such a willingness to take risks and to ride a hype/bubble. For most AI companies, the US as a location means they are able to raise more at a better (for the founders) valuation.
The error is of the same kind as counting the number of papers published by a researcher, or an institution, or an entire country, as some kind of indication for the quality of the research in those papers.
After all, if we just counted publications in AI journals, China, which is far ahead of all the rest of the world (with 39.87%, vs 10.03% of the US) would appear to be the leader in AI research. And that's according to Figure 1.1.11 in the report
Here's a link to the report btw:
https://aiindex.stanford.edu/wp-content/uploads/2023/04/HAI_...
I bet most of the startups in the US are concentrated in the SF/Bay Area. Would be stupid to go build something anywhere else in the US unless you already have a strong team/defined product.