The Enterprise Opportunity in the "AI Slowdown"
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Today, on the a daily brief, why this much bellyhold D A I slowdown is actually an opportunity. The A I daily brief is a daily podcast, ted video, about the most important news and discussions in A I to join the conversation, fall to discard, like in our shown notes.

Hello, friends, welcome back to another long reads episode of the AI daily brief. Today, we are connecting the dots between a topic that we have been covering lots on the show, which is this question of whether we're reaching some plates u in the ability to improve performance of elements with the reality of A I as applied to business.

This is something that i've hinted that in previous episodes, but this gives us a chance to dig into IT all the way and to kick off for gonna ad, an essay by army olson called A I slowdown is everyone else's opportunity. Businesses will benefit from some much needed breathing space to figure out how to deliver that all important return on investment. So first, let's read the piece.

And yes, IT is actually me, not eleven labs me, who will read IT. And then we will do a little bit of a discussion. The multitrillion dollar artificial intelligence boom was built.

Uncertainty that generated models would keep getting exponentially Better. Spoiler ler, they aren't in simple term scaling laws said that if you throw more data in computing power at A I model, capabilities would continuously grow. But a recent flurry of press report suggests that that's no longer the case.

And A S leading developers are finding their models aren't improving as ramages ally as they used to open the eyes. Ryan isn't that much Better at coding than the company's last flagship model, G P, T four. According to bloomberg news, while google is seeing only incremental improvements to its mini software, anthropic, a major rival of both companies, has fAllen behind on the release of its long waited claude model.

Executives that OpenAI, anthropic and google all told me without hesitation recent months that AI development was not platoon, but they would say that the truth is that long health fears of diminishing returns for general AI predicted even by bill gates, are becoming real in the a suits giver. N A, I icon who popularized the bigger is Better approached to building large language models recently told reuters that he had level off the twenty tens with the age of scaling. He said, now we're back in the age of wonder discovery once again.

Wondering discovery puts quite a positive spin on we have no idea what to do next he could also understandable, ably Spark anxiety attacks for investors and businesses who are expected spend one trillion dollars on the inflections needed to deliver on A S promise to transform everything, while street banks, hedge funds in private equity firms are spending billions on funding the build out of vast data centers, according to a recent bloomberg news investigation. Does this all add up to a terrible gamble? Not exactly.

There's no question that the main beneficiaries of the AI boom have been the world's largest tech companies. Quarterly cloud storage revenue for microsoft, google and amazon has been growing at a steady clip, and their market capitalizations, along with those of invidia, apple and meta, have sorted by eight trillion and aggregate over the last two years. Returns on investment for everyone else.

Their customers are taking longer to show up yet a break in the market hype around day. I could be useful just as it's been for previous innovations. That's because technology doesn't typically a brick well and die, but goes through an s curve.

The idea of the s curve is that initial progress takes years before rapidly accelerating as we've seen over the last two years with general ai before IT starts to slow again and crucially, evolve critics over the years, for instance, regularly declared more law debt just before a manufacturing breakthrough for chips pushed IT forward again. The development of airplanes progressed that a coastal pace until the transition from propellers to jets in the late one thousand nine hundred fifties, LED to elite forward, before the technology seemed to play to. But just like chip manufacturing, aviation development install the transform passenger planes that become far more few, efficient, safer and cheaper to Operate, even if they're only nominally faster than they were in the one thousand nine hundred and sixty.

A similar to platter for A I and its scaling laws also might mean a new approach to development and measuring success, which until now has focus too much on capability and not enough on other areas such as safety. Some of the most advanced generate A I models fall short on critical areas like security and fairness. According to a recent academic study that measured how well they follow a of upcoming AIGC for much of this year already, A I researchers have been looking at new paths for improving their models that don't just involve throwing more data and computing power at them.

One approaches to focus in handing a model after IT has been trained in the so called inference phase. This can involve giving a model extra time to process multiple possibilities before settle on an answer. And it's why OpenAI describe its most recent model.

A one is being Better at reasoning. The beauty of the s curve is that I can give everyone else some breathing room instead of cAmberton for the latest tech that will give them in edge over their competitors. Companies that have been experimenting with generate A I and grappling with ways to boost their productivity now have time to redesign their workplace and business processes to Better capitalized on current AI models, which are powerful.

Remember, IT took years for businesses to reorganize themselves around computers in the one thousand nine and eighties. Stanford, the university professor erik brain ellsling, writing on the productivity paradox, points out that output often appears to stall or drop with major new technologies arrive before surging. A pause for A I gives businesses more space in that all important investment phase.

IT also gives regulators time to design more effective guard rails. The european union ai act, which companies will be subject to from twenty twenty six, needs to be more specific how IT defines harms as standards bodies do that work. IT helps that new final models leading to a batch of unexpected problems aren't about to flood the market.

Generative A I has been on a bullet train during the past two years, and the momentum has clearly been lucrative for tech giants. Slowdown at the station offers a much needed break for everyone else. Today's episode is brought to you by vantage, whether you're starting or scaling your company security program, demonstrating top noch security practices and establishing trust is more important than ever.

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Learn more. Ventadour com slash N L W that's ventadour com slash N W today's episode is brought to you, as always, by super intelligent. Have you ever wanted an A I daily brief, but totally focused on how A I relates to your company? Is your company struggling with the A I adoption, either because you're getting installed, figuring out what use cases will drive value or because the A I transformation that is happening isolated individual teams, departments and employees and not able to change the company as a whole?

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That's be super at A I slash partner, all right. So that is the peace. And of course, what I want to honing on is this framing of the idea that this can be a opportune moment, particularly for business. I'm going to hold aside the discussion of guard rails and policy in the european union that and instead focus on this idea that enterprises and big companies have been struggling to catch up to th Epace o f g eneral a i.

And on this point, there is absolutely no debate, even the organizations that right now feel that they are far ahead of their competitors still feel behind relative to the opportunity that lies in front of if you look at the speed with which big business has adopted, generate A I fully embracing its potential, attempting to create new structures to integrate IT. IT is easily the fastest adoption cycle that we've ever seen when IT comes to technology in the enterprise. And yet IT still lacks simply because of how totally all encompassing the change really is.

This is not a shift from A P, A, I set of business processes to a post A, I set of business processes. IT is a paradise shift in how often, how broadly and how deeply organizations have to change. A I, by definition, is a technology that speeds up its own next development.

Just as enterprises get comfortable with one new set of workload, something totally new is going to be coming down the pipeline. And that's why adoption and utilization can be thought of as a one time process instead of new infrastructure for ongoing adaptation is what's required. And I agree that to the extent that we are actually getting to a model, plat toe IT gives enterprises and organizations the chance to get a little closer to building that infrastructure and the systems that come with IT to actually keep up with th Epace o f i nnovation i n g eneral.

A I, so what does this mean in practice though? Well, I think I mean a couple of things. First of all, I think that the enterprises that succeed are going to be the ones who do view this as not a one time shift, but a new Operational modality and who endeavor to go build systems for change systems by which they can integrate new business processes, understand what's working on what isn't, and quickly scale what is working across the whole organization.

Another thing that I believe a separate business winners from losers in this transition is going to be in how different companies to find success, those who to find A I strictly as an efficiency technology and are content with the same outputs, just with fewer inputs or faster inputs. I think you're going to be initially thrilled and then later disappointed. They're going to be disapointment.

They going to see their peers who instead view A I as an opportunity creation technology race ahead of them, offering new products, new services, a new layer of important success, never before possible, and generally embrace the transformative capabilities of A I, rather than just hoping that makes what they do cheaper. The question, of course, is how if you are an organization who believes all these things that i'm saying organizations need to believe, how do you put them into practice? In a word, its systems, systems, systems, systems.

You need systems for examining and reviewing all existing business workload and processes on an individual team, business unit, department, whatever, all the levels. Second, you need a system and an infrastructure for understanding what the alternatives are and how those alternatives change. Week over weekend, months over month.

You need the ability to map all of these new offerings against what people are already doing and also against what people wish that they could be doing. Enterprises need systems for monitoring all of the experiments that are happening, both big and small, again, on an individual level and on a team level. They need systems in tools for processing all the information that comes out of those experiments and pilots and determines what the new set of insights and best practices and new improved processes are.

Enterprises need systems to scale that, systems for taking what is working and spreading IT. Theoretically, the moment that someone discovers an incredibly valuable new use case in one part of the organization, there really shouldn't be very many barriers getting that everywhere across the organization in short order. Of course, there are when you don't have systems.

Now of course, this is directly what we are spending all of our time on super intelligence on. So I am pretty deep in the weeds with what these types of systems might look like in the future. However, as with so much, I think the answer is not to get IT perfect, but to start by starting and just move.

Ultimately, what this S A says in the point that I agree with is that to the extent that there is a reprieve in the speed of technological innovation, IT is one that should not be used to slow down and catch your institutional breath, but instead to try to race and make up some of the distance between where you are and where A I is. Both me and super intelligence are, of course, around if you need any help on that journey. But for now, that is going to do IT for today's a daily brief. Appreciate you listening as always. Hope you're having in a great weekend till next time, please.