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Comment by mellosouls | Hacker News Reader

The report homepage:

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:

https://news.ycombinator.com/item?id=35431057

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If the top ten takeaways are ok using incredibly vaporous, non-sensical phrasing why would I dig any deeper?

“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.

Not decommissioning one jet: just one fraction of a percent of one jet ride.

Honestly seems like a good tradeoff.

The utility of effective models (which can be used many times over) likely exceeds the utility of virtually any person travelling anywhere one time. That seems like a poorly thought statistic to mention. It makes me wonder if it’s misunderstood or misinterpreted.

Total passengers’ CO2/journey (KG) 292.50 according to https://applications.icao.int/icec/Home/Index

This is roughly a 400 mile car trip, or about a year of breathing.

Those are 100% not comparable metrics.

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.

not comparable from a climate change perspective, but helps put perspective into just how much CO2 that is. I disagree with you that it's unhelpful, context is always helpful.

> 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

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!

I agree! So many more possibilities too, like for example rather than simply downloading and locally storing the movie Predator once I am forced to hunt down a provider who currently has it and stream it directly each time I want to watch it. Between google, the streaming provider, the cost of all the extra networking equipment required to support this data, and the extra cost on end-user devices themselves I wonder what the carbon cost of copyright is?

They are using it as an example but, if you take all of the training across all organizations it represents a huge carbon footprint due to training. Also, inference isn't exactly free either . Open sourcing your weights and putting them downloadable would get rid of that but on the other hand you have trade secrets that would make you not want to release your weights so inevitable another group will reproduce your weights and use more electricity.

I wonder how the carbon footprint of training every single large language model that exists today compares to the carbon footprint of a single day of global air traffic.

That question is unanswerable so its weird to wonder about it...

Is it? I wonder about unanswerable questions all the time.

What's answerable isn't even clear in advance most of the time, for many scientific, philosophical, and mathematical questions! Questions that are not obviously answerable often turn out to be really productive, important, or interesting, too.

I bet it's a smaller carbon footprint than dogecoin.

Execs won't read it until someone turns it into a 100-slide powerpoint and emails it to them.

I hate how correct this is. LOL

I've been told by multiple McKinsey people that execs won't read a god-damn thing unless it's, specifically, in a powerpoint deck. Typically never intended to be presented, even, often just these hideous walls of text copy-pasted into the deck then emailed around, often with tons and tons of slides.

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?

To be fair, I've (tried to) read some articles that McKinsey puts out and it's just thousands upon thousands of words of rambling.

Forcing things onto a PPT forces clarity due to the form factor, not unlike a twitter thread.

We need a plugin to have ChatGPT read it and resume it on a 5 line post....

You can upload a pdf of the report to www.chatpdf.com and query it.

Thanks for chatpdf.com I found it very useful

Welcome.

Checkout sitegpt as well if you want to create a query bot for your website.

This is what Kagi's Universal Summarizer[0] generates[1]:

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...

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