Every year, Stanford puts out an AI Index1 with a massive amount of data attempting to sum up the current state of AI.
In 2022, it was 196 pages; last year, it was 386; now, it’s over 500 ... The report details where research is going and covers current specs, ethics, policy, and more.
It is super nerdy ... yet, it’s probably worth a skim (or ask one of the new AI services to summarize the key points, put it into an outline, and create a business strategy for your business from the items that are likely to create the best sustainable competitive advantages for you in your industry).
For reference, here are my highlights from 2022 and 2023.
AI (as a whole) received less private investment than last year - despite an 8X funding increase for Generative AI in the past year.
Even with less private investment, progress in AI accelerated in 2023.
We saw the release of new state-of-the-art systems like GPT-4, Gemini, and Claude 3. These systems are also much more multimodal than previous systems. They’re fluent in dozens of languages, can process audio and video, and even explain memes.
So, while we’re seeing a decrease in the rate at which AI gets investment dollars and new job headcount, we’re starting to see the dam overflow. The groundwork laid over the past few years is paying dividends. Here are a few things that caught my eye and might help set some high-level context for you.
Even since 2022, the capabilities of key models have increased exponentially. LLMs like GPT-4 and Gemini Ultra are very impressive. In fact, Gemini Ultra became the first LLM to reach human-level performance on the Massive Multitask Language Understanding (MMLU) benchmark. However, there’s a direct correlation between the performance of those systems and the cost to train them.
The number of new LLMs has doubled in the last year. Two-thirds of the new LLMs are open-source, but the highest-performing models are closed systems.
While looking at the pure technical improvements is important, it’s also worth realizing AI’s increased creativity and applications. For example, Auto-GPT takes GPT-4 and makes it almost autonomous. It can perform tasks with very little human intervention, it can self-prompt, and it has internet access & long-term and short-term memory management.
Here is an important distinction to make … We’re not only getting better at creating models, but we’re getting better at using them. Meanwhile, the models are getting better at improving themselves.
Researchers estimate that computer scientists could run out of high-quality language data for LLMs by the end of this year, exhausting low-quality language data within two decades, and use up image data by the late 2030s. This means we’ll increasingly rely on synthetic data to train AI systems. The call to rely on Synthetic data can be compelling, but when used as the majority of a data set, it can result in model collapse.
With limited large datasets, fine-tuning has grown increasingly popular. Adding smaller but curated datasets to a model’s training regimen can boost overall model performance while also sharpening the model’s capabilities on specific tasks. It also allows for more precise control over behavior.
Better AI means better data, which means ... you guessed it, even better AI. New tools like SegmentAnything and Skoltech are being used to generate specialized data for AI. While self-improvement isn’t possible yet without intervention, AI has been improving at an incredible pace.
The adoption of AI and the claims on AI “real estate” are still increasing. The number of AI patents has skyrocketed. From 2021 to 2022, AI patent grants worldwide increased sharply by 62.7%. Since 2010, the number of granted AI patents has increased more than 31 times.
As AI has improved, it has increasingly forced its way into our lives. We’re seeing more products, companies, and individual use cases for consumers in the general public.
While the number of AI jobs has decreased since 2021, job positions that leverage AI have significantly increased.
As well, despite the decrease in private investment, massive tranches of money are moving toward key AI-powered endeavors. For example, InstaDeep was acquired by BioNTech for $680 million to advance AI-powered drug discovery, Cohere raised $270 million to develop an AI ecosystem for enterprise use, Databricks bought MosaicML for 1.3 Billion, and Thomson Reuters acquired Casetext - an AI legal assistant.
Not to mention the investments and attention from companies like Hugging Face, Microsoft, Google, Bloomberg, Adobe, SAP, and Amazon.
Unfortunately, the number of AI misuse incidents is skyrocketing. And it’s more than just deepfakes, AI can be used for many nefarious purposes that aren’t as visible, on top of intrinsic risks, like with self-driving cars. A global survey on responsible AI highlights that companies’ top AI-related concerns include privacy, data security, and reliability.
When you invent the car, you also invent the potential for car crashes ... when you ‘invent’ nuclear energy, you create the potential for nuclear weapons.
There are other potential negatives as well. For example, many AI systems (like cryptocurrencies) use vast amounts of energy and produce carbon. So, the ecological impact has to be taken into account as well.
Luckily, many of today’s best minds are focused on creating bumpers to rein in AI and prevent and discourage bad actors. The number of AI-related regulations has risen significantly, both in the past year and over the last five years. In 2023, there were 25 AI-related regulations, a stark increase from just one in 2016. Last year, the total number of AI-related regulations grew by 56.3%. Regulating AI has become increasingly important in legislative proceedings across the globe, increasing 10x since 2016.
Not to mention, US government agencies allocated over $1.8 billion to AI research and development spending in 2023. Our government has tripled its funding for AI since 2018 and is trying to increase its budget again this year.
Conclusion
Artificial Intelligence is inevitable. Frankly, it’s already here. Not only that ... it’s growing, and it’s becoming increasingly powerful and impressive to the point that I’m no longer amazed by how amazing it continues to become.
Despite America leading the charge in AI, we’re also among the lowest in positivity about the benefits and drawbacks of these products and services. China, Saudi Arabia, and India rank the highest. Only 34% of Americans anticipate AI will boost the economy, and 32% believe it will enhance the job market. Significant demographic differences exist in perceptions of AI’s potential to enhance livelihoods, with younger generations generally more optimistic.
We’re at an interesting inflection point where fear of repercussions could derail and diminish innovation - slowing down our technological advance.
Much of this fear is based on emerging models demonstrating new (and potentially unpredictable) capabilities. Researchers showed that these emerging capabilities mostly appear when non-linear or discontinuous metrics are used ... but vanish with linear and continuous metrics. So far, even with LLMs, intrinsic self-correction has shown to be very difficult. When a model is left to decide on self-correction without guidance, performance declines across all benchmarks.
If we don’t continue to lead the charge, other countries will … you can already see it with China leading the AI patent explosion.
We need to address the fears and culture around AI in America. The benefits seem to outweigh the costs – but we have to account for the costs (time, resources, fees, and friction) and attempt to minimize potential risks – because those are real (and growing) as well.
Pioneers often get arrows in their backs and blood on their shoes. But they are also the first to reach the new world.
Luckily, I think momentum is moving in the right direction. Last year, it was rewarding to see my peers start to use AI apps. Now, many of them are using AI-inspired vocabulary and thinking seriously about how best to adopt AI into the fabric of their business.
We are on the right path.
Onwards!
1Nestor Maslej, Loredana Fattorini, Raymond Perrault, Vanessa Parli, Anka Reuel, Erik Brynjolfsson, John Etchemendy, Katrina Ligett, Terah Lyons, James Manyika, Juan Carlos Niebles, Yoav Shoham, Russell Wald, and Jack Clark, “The AI Index 2024 Annual Report,” AI Index Steering Committee, Institute for Human-Centered AI, Stanford University, Stanford, CA, April 2024. The AI Index 2024 Annual Report by Stanford University is licensed under Attribution-NoDerivatives 4.0 International.
New York and Hawaii top the list with 12% and 11.8% respectively. Alaska ends the list with 4.9%, followed by New Hampshire with 5.6%.
Alaskans don't pay state income tax, but neither do Florida, Nevada, South Dakota, Tennessee, Texas, Washington, or Wyoming. So, if you're trying to avoid taxes, they all sound like better bets.
New Hampshire still has a better state tax burden than any of them despite its 4% flat tax on interest and dividend income.
If you don't like paying taxes (and don't mind the cold), then Alaska might be worth the winters?
Meanwhile, we hear a lot about the exodus from California, but not from New York or Maine. Maybe it's the people ... or maybe it's their Governor?
A few years ago, I shared a presentation called Mindset Matters that I had given to a small mastermind group.
This past week, I revisited that content in a different group.
One of my core beliefs is that energy is one of the most important things we can measure. I believe it so strongly I paid Gaping Void to put it on my wall.
It means exactly what it sounds like - but also a lot more.
Energy affects how you feel, what you do, and what you make it mean. That means it is a great way to measure your values too. Consequently, even if you don’t recognize it, energy has a lot to do with who you hire and fire. It affects where you spend your time. Ultimately, it even affects the long-term vision of our company. If something brings profit and energy, it is probably worth pursuing.
In contrast, fighting your energy is one of the quickest ways to burn out. Figuring out who and what to say “no” to is a crucial part of making sure you stay on the path and reach your goals.
I believe that words have power. Specifically, the words you use to describe your identity and your priorities change your reality.
First, some background. Your Roles and Goals are nouns. That means “a person, place, or thing.” Let's examine some sample roles (like father, entrepreneur, visionary, etc.) and goals (like amplified intelligence, autonomous platform, and sustainable edge). As expected, they are all nouns.
Next, we’ll examine your default strategies. You use these in order to create or be the things you want. The strategies you use are verbs. That means they define an action you take. Action words include: connect, communicate, contribute, collaborate, protect, serve, evaluate, curate, share … and love. On the other end of the spectrum, you could complain, retreat, blame, or block.
People have habitual strategies. I often say happy people find ways to be happy – while frustrated people find ways to be frustrated. This is true for many things.
Seen a different way, people expect and trust that you will act according to how they perceive you.
Meanwhile, you are the most important perceiver.
Another distinction worth making is that the nouns and verbs we use range from timely to timeless. Timely words relate to what you are doing now. Timeless words are chunked higher and relate to what you have done, what you are doing, and what you will do.
The trick is to chunk high enough that you are focused on words that link your timeless Roles, Goals, and Strategies. When done right, you know that these are a part of what makes you … “You”.
My favorite way to do this is through three-word strategies.
These work for your business, priorities, identity, and more.
I’ll introduce the idea to you by sharing my own to start.
Understand. Challenge. Transform.
The actual words are less important than what they mean to me.
What’s also important is that not only do these words mean something to me, but I’ve put them in a specific order, and I’ve made these words “commands” in my life. They’re specific, measurable, and actionable. They remind me what to do. They give me direction. And, together, they are a strategy (or process) that creates a reliable result.
First, I understand, because I want to make sure I consider the big picture and the possible paths from where I am to the bigger future possibility that I want. Then, I challenge situations, people, norms, and more. I don’t challenge to tear down. I challenge to find strengths … to figure out what to trust and rely upon. Finally, I transform things to make them better. Insanity is doing what you always do and expecting a different result. This is about finding where small shifts create massive consequences. It is about committing to the result rather than how we have done things till now.
If I challenged before I knew the situation, or I tried to transform something without properly doing my research, I’d risk causing more damage than good.
Likewise, imagine the life of someone who protects, serves, and loves. Compare that to the life of someone who loves, serves, and protects. The order matters!
There is an art and a science to it. But it starts by taking the first step. Try to find your three words.
I’ve set daily alarms on my phone to remind me of these words. I use them when I’m in meetings, and they’re used to evaluate whether I’m showing up as my best self.
You can also create three words that are different for the different hats you wear, the products in your business, or how your team collaborates.
Like recipes, your words should have ingredients, orders, and intensities. As you use your words more, the intensities might change. For example, when my son was just getting out of college, one of his words was contented because he was focused on all the things he missed from college - instead of being appreciative of the things he had. Later, his words switched to grateful and then loving. Evolutions that paired with his personal journeys and represented stronger actions.
Realize that we create what we want by doing. As such, choose words that inform or spark the right actions. You can see that in my son’s words. As he grew, he became more comfortable actively prompting the actions he wanted to approach life with, instead of just passively hoping for a feeling.
You can apply these simple three-word strategies almost everywhere once you learn how to create them.
The problem with history is it rarely tells the whole story.
Ideally, history would be presented objectively, recounting facts without the influence of societal bias, the perspective of the victor, or the storyteller's slant. But achieving this is harder than it seems.
Think about your daily life – it is filled with many seemingly innocuous judgments about your perception of the economy, what's happening in the markets, who is a hero, who deserves punishment, and whether an action is "Just" or "Wrong".
I'm often surprised by how frequently intelligent people violently disagree on issues that seem clear-cut to them.
It's like a fish in water not realizing it's in water ... Most people don't realize the inherent biases and filters that inform their sense of the world or reality.
This post is an attempt to highlight the importance of diverse perspectives and information sources in building well-informed viewpoints.
Even though most people would agree that genuinely understanding history requires a clear picture, free from bias ... I think it's apparent that history (as we know it) is subjective. The narrative shifts to support the needs of the society reporting it.
The Cold War is a great example where: during the war, immediately after the war, and today, the interpretation of the causes and events has changed.
But while that's one example, to a certain degree, we can see it everywhere. We can even see it in the way events are reported today. News stations color the story based on whether they're red or blue, and the internet is quick to jump on a bandwagon even if the information is hearsay.
Now, what happens when you can literally rewrite history?
“Every record has been destroyed or falsified, every book rewritten, every picture has been repainted, every statue and street building has been renamed, every date has been altered. And the process is continuing day by day and minute by minute. History has stopped.“ - Orwell, 1984
That's one of the potential risks of deepfake technology. As it gets better, creating "supporting evidence" becomes easier for whatever narrative a government or other entity is trying to make real.
On July 20th, 1969, Neil Armstrong and Buzz Aldrin landed safely on the moon. They then returned to Earth safely as well.
MIT recently created a deepfake of a speech Nixon's speechwriter William Safire wrote during the Apollo 11 mission in case of disaster. The whole video is worth watching, but the speech starts around 4:20.
Can you imagine the real-world ripples that would have occurred if the astronauts died on that journey (or if people genuinely believed they did)? Here is a quote from the press response the Nixon-era government prepared in case of that disaster.
"Fate has ordained that the men who went to the moon to explore in peace will stay on the moon to rest in peace." - Nixon's Apollo 11 Disaster Speech
Today, alternative histories are becoming some people's realities. Why? Media disinformation is the cause and is more dangerous than ever.
Alternative history can only be called that when it's discernible from the truth, and unfortunately, we're prone to look for information that already fits our biases.
Today, we also have to increasingly consider the impacts of technology. Deepfakes are becoming more commonplace - with popstar Drake even using AI in a recent record. Now, that was apparent - but scarily, research shows that most can't tell a deepfake from reality (even if they think they can.)
As deepfakes get better, we'll also get better at detecting them, but it's a cat-and-mouse game with no end in sight.
In Signalling theory, it's the idea that signallers evolve to become better at manipulating receivers, while receivers evolve to become more resistant to manipulation. We're seeing the same thing in trading with algorithms.
In 1983, Stanislav Petrov saved the world. Petrov was the duty officer at the command center for a Russian nuclear early-warning system when the system reported that a missile had been launched from the U.S., followed by up to five more. Petrov judged the reports to be a false alarm and didn't authorize retaliation (and a potential nuclear WWIII where countless would have died).
But messaging is now getting more convincing. It's harder to tell real from fake. What happens when a world leader has a convincing enough deepfake with a convincing enough threat to another country? Will people have the wherewithal to double-check? What about when they're buffeted by these messages constantly and from every direction?
As we increasingly use AI for writing and editing, there is a growing risk of subtle changes being made to messages and communications. This widespread opportunity to manipulate information amplifies the capacity and potential for people to use these technologies to influence people's perceptions. As a result, we must be increasingly cautious about how the data we rely on may be altered, which could ultimately affect our perceptions and decisions.
Despite the risks, I'm excited about the promise and the possibilities of technology. But, as always, in search of the good (or better), we have to acknowledge and be prepared for the bad.
In 2020, I had a Zoom meeting with Matthew Piepenburg of Signals Matter. Even though it was a private discussion, there was so much value in our discussion we decided to share parts of it online.
Four years later, I still think it's a great watch.
While Matt evaluates markets based on Macro/Value investing, I'm much more interested in advanced AI and quantitative methods.
As you might expect, there are a lot of differences in how we view the world, decision-making, and the market. Nonetheless, we share a lot of common beliefs as well.
Our talk explores several interesting areas and concepts. I encourage you to watch it below.
Even though this video is four years old, the lessons remain true – markets are not the economy, and normal market dynamics have been out the window for a long time. In addition, part of why you're seeing increased volatility and noise is because there are so many interventions and artificial inputs to our market system.
While Matt and I may approach the world with very different lenses, we both believe in "timeless wisdom".
Ask yourself, What was true yesterday, today, and will stay true tomorrow?
That is part of the reason we focus on emerging technologies and constant innovation ... they remain relevant.
Something we can both agree on is that if you don't know what your edge is ... you don't have one.
Hope you enjoyed the video.
Let me know what other topics you'd like to hear more about.
It's a pretty damning video from someone who is frustrated with AI - but it makes several interesting points. The presenter discusses Amazon's recent foible, Google's decreasing search quality, the increase of poorly written AI-crafted articles, GPTs web-scraping scandals, and the overall generalization of responses we see as everyone uses AI everywhere.
Yanshin attributes the disparity between the actual results and the excitement surrounding AI stocks to the substantial investments from technology giants. But as most bubbles prove, money will be the catalyst for amazing things — and some amazing failures and disappointments too.
His final takeaway is that, regardless of its current state, AI is coming and will undoubtedly improve our lives.
If I were to add some perspective from someone in the industry, it would be this.
AI Is Overdelivering in Countless Ways
There will always be a gap between expectations and reality (because there will always be a gap between the hype and adoption cycles). AI is already seamlessly integrated into your life. It's the underpinning of your Smartphones, Roombas, Alexas, Maps, etc. It has also massively improved supply chain management, data analytics, and more.
That's not what gets media coverage ... because it's not sexy ... even if it's real.
Having created AI since arguably the mid-90s, the progress and capabilities of AI today are hard to believe. They're almost good enough to seem like science fiction.
The Tool Isn't Usually The Problem
Artificial Intelligence is not a substitute for the real thing—and it certainly can't compensate for the lack of the real thing.
I sound like a broken record, but AI is a tool, not a panacea. Misusing it, like using a shovel as a hammer, leads to disappointment. And it doesn't help if you're trying to hammer nails when you should be laying bricks.
ChatGPT is very impressive, as are many other generative AI tools. However, they're still products of the data used to train them. They won't make sure they give you factual information; they can only write their responses based on the data they have.
If you give an AI tool a general prompt, you'll likely get a general answer. Crafting precise prompts increases their utility and can create surprising results.
Even if AI independently achieves 80% of the desired outcome, it still did it without a human, a salary, or hours and days of time to create it.
Unfortunately, if you're asking the wrong questions, the answers still won't help you.
That's why it matters not only that you use the right tool but also that you use it to solve the right problem. In addition, many businesses lose sight of the issues they're solving because they get distracted by bright and shiny new opportunities.
Conclusion
Sifting the wheat from the chaff has become more complicated — and not just in AI. Figuring out what news is real, who to trust, and what companies won't misuse your data seems like it has almost become a full-time job.
If you take the time, you will see a lot of exciting progress.
Public perception is likely to trend downward in the next news cycle, which is to be expected. After the peak of inflated expectations comes the trough of disillusionment.
Regardless, AI will continue to become more capable, ubiquitous, and autonomous. The question is only how long until it affects your business and industry.
On one hand, I try not to think about or predict markets (because I recognize the futility of trying to predict something random to me). On the other hand, it is an election year, and my opinion matters as a proxy for what people like me think or feel in an election year. So, with that in mind, I expected to see a brief market correction blamed on various geopolitical instabilities and partisan weaknesses, followed by a long and steady push higher as we approach the November elections.
What do you think? Is the market's move downwards the start of something bigger, or is it just a temporary correction before a push higher into November?
Not to mention, for the past few years, the top 20 stocks have contributed almost exclusively to the success of the S&P 500. In 2023, the top 20 stocks drove 7.08% of the 7.55% return.
Those stocks are almost exclusively AI & Tech Stocks.
Often, people look to the S&P as a sign of the economy, but this is a helpful reminder that markets are not the economy.
As we look at the S&P, it's also interesting to look at the top stocks over the past 40 years. Visual Capitalist compiled a chart that ranks the top S&P 500 stocks by calendar year returns.
Qualcomm's 2620% return in 1999 is hard to imagine, especially with Tesla's 743% percent growth from 2020 being a distant 2nd place.
In case you were wondering, Qualcomm's growth in 1999 was primarily driven by patents for Code Division Multiple Access (CDMA) technology, which was the infrastructure for "fast" wireless internet access and the 3G network.
A Few Graphs On The State of AI in 2024
Every year, Stanford puts out an AI Index1 with a massive amount of data attempting to sum up the current state of AI.
In 2022, it was 196 pages; last year, it was 386; now, it’s over 500 ... The report details where research is going and covers current specs, ethics, policy, and more.
It is super nerdy ... yet, it’s probably worth a skim (or ask one of the new AI services to summarize the key points, put it into an outline, and create a business strategy for your business from the items that are likely to create the best sustainable competitive advantages for you in your industry).
For reference, here are my highlights from 2022 and 2023.
AI (as a whole) received less private investment than last year - despite an 8X funding increase for Generative AI in the past year.
Even with less private investment, progress in AI accelerated in 2023.
We saw the release of new state-of-the-art systems like GPT-4, Gemini, and Claude 3. These systems are also much more multimodal than previous systems. They’re fluent in dozens of languages, can process audio and video, and even explain memes.
So, while we’re seeing a decrease in the rate at which AI gets investment dollars and new job headcount, we’re starting to see the dam overflow. The groundwork laid over the past few years is paying dividends. Here are a few things that caught my eye and might help set some high-level context for you.
Technological Improvements In AI
via AI Index 2024
Even since 2022, the capabilities of key models have increased exponentially. LLMs like GPT-4 and Gemini Ultra are very impressive. In fact, Gemini Ultra became the first LLM to reach human-level performance on the Massive Multitask Language Understanding (MMLU) benchmark. However, there’s a direct correlation between the performance of those systems and the cost to train them.
The number of new LLMs has doubled in the last year. Two-thirds of the new LLMs are open-source, but the highest-performing models are closed systems.
While looking at the pure technical improvements is important, it’s also worth realizing AI’s increased creativity and applications. For example, Auto-GPT takes GPT-4 and makes it almost autonomous. It can perform tasks with very little human intervention, it can self-prompt, and it has internet access & long-term and short-term memory management.
Here is an important distinction to make … We’re not only getting better at creating models, but we’re getting better at using them. Meanwhile, the models are getting better at improving themselves.
The Proliferation of AI
First, let’s look at patent growth.
via AI Index 2024
The adoption of AI and the claims on AI “real estate” are still increasing. The number of AI patents has skyrocketed. From 2021 to 2022, AI patent grants worldwide increased sharply by 62.7%. Since 2010, the number of granted AI patents has increased more than 31 times.
As AI has improved, it has increasingly forced its way into our lives. We’re seeing more products, companies, and individual use cases for consumers in the general public.
While the number of AI jobs has decreased since 2021, job positions that leverage AI have significantly increased.
As well, despite the decrease in private investment, massive tranches of money are moving toward key AI-powered endeavors. For example, InstaDeep was acquired by BioNTech for $680 million to advance AI-powered drug discovery, Cohere raised $270 million to develop an AI ecosystem for enterprise use, Databricks bought MosaicML for 1.3 Billion, and Thomson Reuters acquired Casetext - an AI legal assistant.
Not to mention the investments and attention from companies like Hugging Face, Microsoft, Google, Bloomberg, Adobe, SAP, and Amazon.
Ethical AI
via AI Index 2024
Unfortunately, the number of AI misuse incidents is skyrocketing. And it’s more than just deepfakes, AI can be used for many nefarious purposes that aren’t as visible, on top of intrinsic risks, like with self-driving cars. A global survey on responsible AI highlights that companies’ top AI-related concerns include privacy, data security, and reliability.
When you invent the car, you also invent the potential for car crashes ... when you ‘invent’ nuclear energy, you create the potential for nuclear weapons.
There are other potential negatives as well. For example, many AI systems (like cryptocurrencies) use vast amounts of energy and produce carbon. So, the ecological impact has to be taken into account as well.
Luckily, many of today’s best minds are focused on creating bumpers to rein in AI and prevent and discourage bad actors. The number of AI-related regulations has risen significantly, both in the past year and over the last five years. In 2023, there were 25 AI-related regulations, a stark increase from just one in 2016. Last year, the total number of AI-related regulations grew by 56.3%. Regulating AI has become increasingly important in legislative proceedings across the globe, increasing 10x since 2016.
Not to mention, US government agencies allocated over $1.8 billion to AI research and development spending in 2023. Our government has tripled its funding for AI since 2018 and is trying to increase its budget again this year.
Conclusion
Artificial Intelligence is inevitable. Frankly, it’s already here. Not only that ... it’s growing, and it’s becoming increasingly powerful and impressive to the point that I’m no longer amazed by how amazing it continues to become.
Despite America leading the charge in AI, we’re also among the lowest in positivity about the benefits and drawbacks of these products and services. China, Saudi Arabia, and India rank the highest. Only 34% of Americans anticipate AI will boost the economy, and 32% believe it will enhance the job market. Significant demographic differences exist in perceptions of AI’s potential to enhance livelihoods, with younger generations generally more optimistic.
We’re at an interesting inflection point where fear of repercussions could derail and diminish innovation - slowing down our technological advance.
Much of this fear is based on emerging models demonstrating new (and potentially unpredictable) capabilities. Researchers showed that these emerging capabilities mostly appear when non-linear or discontinuous metrics are used ... but vanish with linear and continuous metrics. So far, even with LLMs, intrinsic self-correction has shown to be very difficult. When a model is left to decide on self-correction without guidance, performance declines across all benchmarks.
If we don’t continue to lead the charge, other countries will … you can already see it with China leading the AI patent explosion.
We need to address the fears and culture around AI in America. The benefits seem to outweigh the costs – but we have to account for the costs (time, resources, fees, and friction) and attempt to minimize potential risks – because those are real (and growing) as well.
Pioneers often get arrows in their backs and blood on their shoes. But they are also the first to reach the new world.
Luckily, I think momentum is moving in the right direction. Last year, it was rewarding to see my peers start to use AI apps. Now, many of them are using AI-inspired vocabulary and thinking seriously about how best to adopt AI into the fabric of their business.
We are on the right path.
Onwards!
1Nestor Maslej, Loredana Fattorini, Raymond Perrault, Vanessa Parli, Anka Reuel, Erik Brynjolfsson, John Etchemendy, Katrina Ligett, Terah Lyons, James Manyika, Juan Carlos Niebles, Yoav Shoham, Russell Wald, and Jack Clark, “The AI Index 2024 Annual Report,” AI Index Steering Committee, Institute for Human-Centered AI, Stanford University, Stanford, CA, April 2024. The AI Index 2024 Annual Report by Stanford University is licensed under Attribution-NoDerivatives 4.0 International.
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