The AI Daily Brief: Artificial Intelligence News and Analysis - Predictions for Generative AI Year 2

Episode Date: December 3, 2023

Thursday was the one-year anniversary of ChatGPT. NLW reads (with the help of ElevenLabs) a group of predictions around what year 2 for generative AI will look like. Read the predictions: https://www.fastcompany.com/90989785/what-year-2-of-the-generative-ai-craze-will-look-like-according-to-41-experts Today's Sponsors: Listen to the chart-topping podcast 'web3 with a16z crypto' wherever you get your podcasts or here: https://link.chtbl.com/xz5kFVEK?sid=AIBreakdown  ABOUT THE AI BREAKDOWN The AI Breakdown helps you understand the most important news and discussions in AI.  Subscribe to The AI Breakdown newsletter: https://theaibreakdown.beehiiv.com/subscribe Subscribe to The AI Breakdown on YouTube: https://www.youtube.com/@TheAIBreakdown Join the community: bit.ly/aibreakdown Learn more: http://breakdown.network/

Today on the AI breakdown, we're looking at some predictions for what year two of generative AI might bring. The AI breakdown is a daily podcast and video about the most important news and discussions in AI. Go to Breakdown.network for more information about our YouTube, our Discord, and our newsletter. Hello, friends. Welcome back to another weekend episode of the AI breakdown. Now, of course, a big theme of ours for the past few days has been the transition point moment between the first year of generative AI following ChatGPT's release on November 30th, 2022, and what is now the beginning of our second year. We kick that off with a look at ChatGPT's history over the last year, and yesterday we read a bunch of different excerpts from the copious number of op-eds opining on OpenAI or ChatGPT or AI in general, but today we are

firmly facing the future, and we're riffing off of a piece in Fast Company where they asked 41 different business leaders what they thought year two of generative AI was going to look like. So what I'm going to do is I've taken not all of them, but just some of the more interesting comments, and I've organized them into categories. I'm going to tee up each of those categories in each of those posts, but then I will be using the 11 Labs voice library to read the quotes of these different people. Please note these are not the voices of the actual person being quoted. These are, again, just from 11 Labs voice library. The reason I wanted to do it like this is that it's very easy to lose track of who's saying what, and whether it's me or the person being quoted, if it's only my voice across all of these different

quotes. All right, with that said, let's go to the first category, which actually only had one person who mentioned it, which I think is more of a reflection of the fact that the vast majority of people who were asked were more from a traditional business background rather than from the heart of Silicon Valley. But one exception of that was Jeremiah Ow Yang, a partner at Blitzscaling Ventures. Jeremiah says, By the end of 2024, our digital lives will be transformed, starting with our daily communications. every individual at home or work will have an AI agent to manage their emails. Initially, it will filter, highlight, and summarize messages.

As the agent analyzes our history, understands context, and incorporates our feedback, we will, over time, trust it to respond on our behalf using a defined set of guidelines and rules. When you want to really get someone's attention, you may indicate this is an organic artisan email written by me, a human. I think if you had taken a broader survey of Silicon Valley people and entrepreneurs, there would have been much more emphasis on AI agents and autonomy, and all these themes that you see in developer circles every day, day in and day out. Now, easily the biggest theme of this, which again makes sense,

given the context of many of these people being business leaders, was the theme of integration. Now, this is something that I have been harping on for really the last few months, but it is very clear to me that we are moving away from a period in which everything is just about the shiny bells and whistles and the newest new, although we certainly like that too, and much more about how things actually integrate into the way that people are doing their work at the jobs they have currently. Cameron Adams, the co-founder and chief product officer at Canva, sums us up perfectly.

Single-function AI tools like Mid Journey help to bring a focus to generative AI. But in the year ahead, the technology will only truly bridge the gap to the masses. by tools that are integrated into their actual workflows. This won't just change the way that people create or edit images, but also the way they work, helping them to save hours of time with AI workflows that eliminate mundane tasks. It'll enable work they mightn't have even attempted before. Now in terms of where this integration is going to happen, many argue that the first place would be around gaining efficiencies and reducing costs.

Take for example this sentiment from Tim Davis, the co-founder and president of Modular and formerly of Google Brain. I would expect generative AI adoption to accelerate as a reflection of the cost side of the balance sheet with deep penetration across high-cost functions like sales, marketing, customer operations, engineering, and product. You are already seeing this happening

as GeneA.I. revolutionizes content production, customer interactions with chatbots, search engine optimization, product knowledge discovery, engineering code generation, in addition to product design and testing among so many other areas. These are real and direct use cases, not technological hype, and they are delivering incredible business value

that will only quickly accelerate in the months and years ahead. Now, another part of these efficiencies is in reducing monotonous work, as described here by Anna Marie Wagner, the head of AI at Ginkgo Bioworks. Consumer-facing AI tools are getting extremely powerful in areas of obvious judgment. cleaning up mismatched names in a database, for example, or analyzing written survey results that have historically generated huge time sinks for highly skilled employees, such as financial analysts, sales reps, or strategy consultants. Large language models will continue improving on their ability to accurately synthesize

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Beyond crypto and AI, this show is for creators seeking more ways to truly own their work, for business leaders trying to prepare for the future today and for innovators exploring trending tech topics. So go ahead, listen to Web3 with A16Z crypto wherever you get your podcasts. There's also a large sense that in addition to just obvious sort of low-hanging fruit use cases, that the new capacities of generative AI will actually have different divisions think very differently about the way that they interact with their work. Take, for example, this argument from emerging technology analyst at Pitchbook Brendan Burke, who basically says that coding is coming even to non-technical teams.

VC investment in generative AI for coding has increased 357.4% this year to nearly $400 million due to the success of GitHub co-pilot in code recommendations. The ability to automate software development is beginning to reach beyond current software developers to product designers and operational teams. Usage of AI coding tools will become widespread among these functions. next year. Adding to this momentum, new foundation models coming out next year will learn from the entire software development process to make anyone capable of deploying an application from start to finish. Relatedly, David Haber, co-founder and CEO of LaCara, argues that we're going

to see a whole lot more model customization for the enterprise. David says, As AI training costs continue to drop, watch for a major shift. Businesses of all sizes tailoring models like ChatGPT to tackle challenges unique to their operations. Whether it's engineering, marketing or HR, AI models will evolve into specialized assistance. Beyond individual tasks, these AIs will also assist in strategic decisions. It's not just boosting efficiency, it's the start of, a new business playbook being written, akin to the creation of the internet. Now, another theme that was related to integration but a little bit different was a focus

on a number of specific industries and functions that were likely to be impacted by the deeper integration of artificial intelligence. Take, for example, Gunderson Law Firm partner, Katie Gardner, talking about the legal industry. Professional service providers, including lawyers, will need to rethink their business models, especially if they are heavily reliant on revenue generation in areas that can be reliably and efficiently replaced by AI, e.g. document review and diligence. The traditional pyramid model,

where you have a high volume of junior associates doing these tasks, may no longer be economically feasible. There will be widespread upskilling as many tasks will no longer require humans to execute them. Similar to the prior industrial revolution, most existing necessary functions of organizations will transform in a dramatic and material way. Now, one pretty interesting and for me at least unexpected theme was the impact on employees of having access to these tools, or as Chris Betty, the chief digital information officer at Service now explains, the backlash if organizations don't.

According to Chris, generative AI will affect employee expectations for the technology they use at work, becoming table stakes for talent retention. If we don't provide employees with generative AI solutions, I feel like it is asking them to use a typewriter when word processors are available. But on the flip side of that is Joe Atkinson, the chief products and technology officer at PWC, who says, A happier workforce leads to better business outcomes,

and I'm optimistic about the role generative AI will play in contributing to a more personalized employee experience that will increase engagement, satisfaction, and productivity. There's no doubt we'll continue to see companies more aggressively roll-out AI training and experimentation programs next year, alongside growth in the most practical generative AI use cases that save organizations time and money, including more personalized customer support and recommendations, high-quality content generation, and workflow automation. So if you are trying to take a step back and really understand what the through line of all these comments are,

I think that it sort of comes down to the fact that, one, these tools are now everywhere. People have had lots of chance to explore them and experiment with them, and they're using them in their daily personal lives. Two, because of that, they're going to want to bring those things to work. There are a variety of low-hanging fruit, cost-saving, efficiency-creating kind of use cases that are almost certainly going to happen, given that they're already starting to happen now, it only makes sense that they'll expand even more in the next year. However, three, beyond that, there are entirely new ways to integrate AI into complex workflows that are really going to drive totally new opportunities for businesses, as well as

shift how even some think about their own business models. And so, four, the TLDR of it all, is generative AI moving from novelty to something that is deeply integrated across businesses and across the enterprise, and is actually useful. in the workplace, not just in theory. Now, I don't think these are particularly far out there predictions, and in fact, I'll be keeping my eyes out for some even bolder claims, especially as we come down the pike at the end of the year, and people are wont to make such claims.

But for now, that is going to do it for today's AI breakdown. Appreciate you guys listening as always, and until next time, peace.