AI has moved into its era of deployment; throughout 2022 and the beginning of 2023, new large-scale AI models have been released every month. These models, such as ChatGPT, Stable Diffusion, Whisper, and DALL-E 2, are capable of an increasingly broad range of tasks, from text manipulation and analysis, to image generation, to unprecedentedly good speech recognition. These systems demonstrate capabilities in question answering and the generation of text, image, and code unimagined a decade ago, and they outperform the state of the art on many benchmarks, old and new. However, they are prone to hallucination, routinely biased, and can be tricked into serving nefarious aims, highlighting the complicated ethical challenges associated with their deployment.
Although 2022 was the first year in a decade where private AI investment decreased, AI is still a topic of great interest to policymakers, industry leaders, researchers, and the public. Policymakers are talking about AI more than ever before. Industry leaders that have integrated AI into their businesses are seeing tangible cost and revenue benefits. The number of AI publications and collaborations continues to increase. And the public is forming sharper opinions about AI and which elements they like or dislike
AI will continue to improve and, as such, become a greater part of all our lives. Given the increased presence of this technology and its potential for massive disruption, we should all begin thinking more critically about how exactly we want AI to be developed and deployed. We should also ask questions about who is deploying it—as our analysis shows, AI is increasingly defined by the actions of a small set of private sector actors, rather than a broader range of societal actors. This year’s AI Index paints a picture of where we are so far with AI, in order to highlight what might await us in the future. Read More
Tag Archives: Strategy
AI And The Great Bifurcation of 2024
What happens when physics constrains AI?
Today I want to write about what I believe will be the great bifurcation of late 2024 – the splitting of the economy into things that can advance with AI, and things that can’t.
… I believe we are making a dangerous mistake by extrapolating the speed of progress AI can have in a digital world to the speed of progress AI can have on the world in general. Think about this – even if you have the world’s smartest AI, 10x better than a human, there are still things that can’t get that much more productive. Read More
AI: Timelines to Takeoff
Two great resources for those wanting to track the when and the how of AI progress.
AI Timelines is the discussion of how long until various major milestones in AI progress are achieved, whether it’s the timeline until a human-level AI is developed, the timeline until certain benchmarks are defeated, the timeline until we can simulate a mouse-level intelligence, or something else.
AI Takeoff refers to the process of an Artificial General Intelligence going from a certain threshold of capability (often discussed as “human-level”) to being super-intelligent and capable enough to control the fate of civilization. There has been much debate about whether AI takeoff is more likely to be slow vs fast, i.e., “soft” vs “hard”.
Defensibility in the Age of AI
Tl;dr: Companies with technology that allows them to uniquely generate the data needed to train and fine-tune models are well positioned to create enduring value in the age of AI. The best AI companies may be those building in atoms and not just bits.
The pace of development in AI has given many the feeling that the ground is shifting under their feet. While incredibly exciting, this has led to a fair amount of anxiety among entrepreneurs who are wondering if there’s any true defensibility in what they’re building. A battle tested strategy in startups is to build a product that’s at least 10x better, 10x cheaper, or 10x easier than what exists while you march toward a long-term moat. But given how quickly AI development is advancing, a 10x product of last month may be obsolete this month. The fear is real. Read More
This Changes Everything
In 2018, Sundar Pichai, the chief executive of Google — and not one of the tech executives known for overstatement — said, “A.I. is probably the most important thing humanity has ever worked on. I think of it as something more profound than electricity or fire.”
Try to live, for a few minutes, in the possibility that he’s right. There is no more profound human bias than the expectation that tomorrow will be like today. It is a powerful heuristic tool because it is almost always correct. Tomorrow probably will be like today. Next year probably will be like this year. But cast your gaze 10 or 20 years out. Typically, that has been possible in human history. I don’t think it is now. Read More
AI value begins with managing the C-suite conversation
CIOs should know that AI has captured the imagination of the public, including their business colleagues. Dialogue is key to remediating misconceptions and steering the enterprise toward value creation.
Every futurist and forecaster I have talked to is convinced the transformative technology of the next seven years is artificial intelligence. Everyone seems to be talking about AI. Unfortunately, most of these conversations do not lead to value creation or greater understanding. And, as an IT leader, you can bet these same conversations are reverberating throughout your organization — in particular, in the C-suite.
CIOs need to jump into the conversational maelstrom, figure out which stakeholders are talking about AI, inventory what they are saying, remediate toxic misconceptions, and guide the discussion toward value-creating projects and processes. Read More
Could your career be replaced by AI or Automation? We’ve Asked ChatGPT AI.
If you didn’t know already, AI and Automation technology is rapidly advancing, meaning some of our jobs could potentially be at risk!
Yes, you read that right.
Tools like ChatGPT and Midjourney have been making waves in the past few months, and their extraordinary capabilities have sent tech nerds into a frenzy.
… AI will never be able to replace the unique perspective and creativity of humans. But by using this technology, that creativity can be taken to all new heights!
…So, is your job at risk? We asked AI… Read More
AI is Useful for Capitalists but Probably Terrible for Anyone Else
AI is finally useful for business, and everyone is likely underestimating its impact. But unless AI is open-source and truly owned by the end users the future for everyone but the software providers looks grim.
The last time your author opined about the state of artificial intelligence I predicted that commercial success required two things: first, that AI researchers focus on solving a specific business problem, and second, that enough data exists for that specific business problem. The premise for this prediction was that researchers needed to develop an intuition of the business process involved so they could encode that intuition into their models. In other words, that a general-purpose solution would not crack every business problem. This might have been true temporarily, but it’s doomed to be wrong more permanently. I missed a reoccurring pattern in the history of AI: that eventually enough computational power wins. In the same way chess-playing engines that tried to encode heuristics about the game eventually lost to models that had enough computational power, these AI models for “specific business problems” have all just lost to the hundred billion parameters of GPT-3.
I am not known for being overly bullish on technology, but I struggle to think of everyday sorts of business examples where such a large language model would not do well. It is true that in the above example the model did terribly on questions requiring basic arithmetic (converting rent per square foot per month to rent per square metre per year, for example), but these limitations are missing the point. Computers are known to be adequate arithmetic-performing machines (hence the name), and surely future models would correct this and other deficiencies. Artificial intelligence is now generally useful for business, and I am probably not thinking broadly enough about where it will end up.
One decent guess, however, might be augmented intelligence – the idea that AI is best deployed as a tool to increase the power and productivity of human operators rather than replace them. Read More
Algorithms Will Make Critical Talent Decisions in the Next Recession—Here’s How To Ensure They’re the Right Ones
Nearly all HR leaders say their department will use software and algorithms to reduce labor costs in a 2023 recession, but only half are completely confident their tech will produce unbiased recommendations.
Entering 2023, the dreaded “R” word—recession—is top of mind for companies around the country. In a Capterra survey of 300 HR leaders in the U.S., 72% say their employer has already started preparing for a possible recession, while 24% plan to start preparing soon.*
As in previous economic downturns, organizations will need to figure out ways to reduce labor costs, including deciding which employees to lay off if it comes to that. Where 2023 differs is that HR is both more strategically involved in these high-level labor decisions and more data-driven than ever before, supported by cutting-edge HR software systems that can aggregate massive amounts of employee information and turn it into actionable insights and recommendations. Read More
Rick's Cafe AI 