The Six Five team discusses Sequoia/A16Z/Goldman rain on the AI parade.
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Transcript:
Daniel Newman: this past week, this has been my new hill to die on, has been an endless call from market makers and market influencers like Andreessen Horowitz and Goldman Sachs and Sequoia.
Sequoia published a piece called AI’s $600 billion problem or challenge. A16Z did a version of this over a series of a few blogs. Goldman Sachs basically came out and said there isn’t a single application on generative AI that basically delivers any value, more or less. The words, those are paraphrases, but those are the words. And so I’ve been thinking a lot about it. I wrote an op-ed, I wrote a few tweets that could have been op-eds. We’re doing a lot of market assessment right now, market growth. If there is $200 billion in CapEx and we need $600 billion in market impact, how does this work? And so I’ve been talking about of these network effects and basically this $200 billion has all been seen by the compute memory systems network. And then of course there’s some power and other elements that have gone into this build-out.
And then you’ve seen where’s all that spend going and that’s where a lot of red flags, people have been somewhat critical of Google, Microsoft, AWS, this wave of startups I mentioned CoreWeave, Lambda Labs and others that are spending a fortune and trying to understand what services are they delivering that people are paying for to justify those huge expense outlays. And then Pat, really the big part is we’re hearing terms now like is software dead or software as we know it is dying? And that’s basically all the ISVs saying that Salesforce, UI path, Workday, ServiceNow, SAP, parts of the Oracle stack, Snowflake, go down that list and say is it the end for them. I mean they’ve been crushed in the market. So there’s been all this excitement and exuberance and enthusiasm about tech’s boom. It hasn’t been all of tech. It’s been like seven companies.
And so a number of companies are being left in the dust with software being a big part of it. But here’s my thesis, Pat. The $600 billion comes from a third network layer that is effectively analyst firms, manufacturing companies, automotive makers, financial services providers, healthcare firms, investment and financial services banks, and they’re going to be using apps, Pat. They run custom software and they run Oracle, they run SAP, they run Salesforce, they run a whole boatload of workloads and apps and guess what? They do a lot of it in the cloud consumption. They do a lot of it in applications, the ones I mentioned. So what we have is an ingestion and then digestion problem. We’re ingesting all this, we’re digesting all of this and basically we’re looking at a time horizon. And so my ultimate thesis here, Pat, is that there isn’t a $600 billion problem.
There is a timeline problem, but if you’re in the market, the timeline problem is more substantial than if you’re in the business because in the market you’re trying to time a trade, you’re getting in, you’re getting out. Am I buying high? Am I buying low? When’s the growth going to come? When am I going to be able to see it in the numbers? One of my favorite lines from one of my favorite movies was called The Big Short, and he walks into the office and he says, “I may be early, but I’m not wrong.” And the guy in front of him says, “It’s the same thing.” It’s the same thing. So if you’re a trader, you are possibly early. Software may be slow to be able to define revenue and then discern between what’s growth of revenue and what’s commodity, Pat. Do AI PCs and phones mean more revenue over the long run or do people just expect more features? And that’s the expectation.
Patrick Moorhead: Oh, you’re on mute again buddy.
Daniel Newman: The other side of it is with SaaS it’s the same thing because the whole SaaS concept was it was born on continuous improvement. So when do people pay for generational quality leaps in software and when is something just supposed to be a baked in feature that’s better. All right, I’m let the topic lie here. Pat, I think if you are a builder, you’re very excited and enthused about the future. I think if you’re trying to trade this, it’s hard to get away from those first network effects because it’s not obvious yet where money’s going to be made.
Patrick Moorhead: I believe this is a hundred percent about timing and it’s hard to see the beauty of the wood finish when you’re putting the plumbing in and building the cement foundation. And when it comes to the infrastructure, that’s exactly what we’re doing and we’re actually having to train the home builders on a new way to build a home and new way to install the cabinets on there ’cause it’s never been done like this before. The one element and maybe you hit, maybe you didn’t, I didn’t interpret it that is competitively. I mean, what is a SaaS provider going to do? Just say, “You know what? I am deciding that I’m just going to not do this right now because I don’t see this thing panning out for another two years”, and all your competitors go in and they institute all of these features and then you’re going to lose all of this business and your stock’s going to get dumped and you’re going to get fired as a CEO and a leadership team.
So there actually is no choice. I think it is a miracle at how these SaaS companies are walking on this razor’s edge of not bringing in a ton of cost and slowly and quickly bringing these features out. One thing I know though, like Adobe Firefly and the ability to cut your content creation costs by 50%, the ability in human resources or any type of service environment to improve self-service in a way we’ve never seen before. I mean, it is just crazy the amount of code that can be written. I mean, heck, agents create code on its own now it’s Sandboxed first to keep it from doing weird and nefarious stuff, but it’s there.
So it’s a timing issue. If you’re an enterprise writing your own enterprise applications and capabilities or you’re an enterprise SaaS companies, what are you going to do? You going to not do e-commerce? Are you not going to put up a website? You not going to connect to the internet. We’ve had these types of milestones before and I know there’s been, listen, I was 10 years into my career when .com boom hit and the bust hit and I think we’re so far away from that. I mean, the internet people, there wasn’t good content on there. I mean it was like you get on and you do search and the search sucked. Why? Because a lot of the content wasn’t even on the internet. I am actually quite optimistic and quite bullish. I will let the financial bean counters figure out the timing and the affordability, but you don’t have a choice if you’re an enterprise or an enterprise SaaS company, you got to move.
Daniel Newman: Yeah, you’re getting into it. And that was what I was saying about what’s expected Pat or required to stay competitive versus what can you actually incrementally charge more for is what I was trying to allude to is of course –
Patrick Moorhead: Everybody but Zoom and a couple other companies are paying. It’s an extra added feature.
Daniel Newman: And so when will people pay for it and do they get enough value to justify? These companies have always just raised prices anyway just for doing iterative feature growth and expansion. That’s the whole model of SaaS, Pat. Now, one thing I know you love to talk about, and we’re going to get to the last topic here, but you’ve always loved to talk about that hybrid multi-cloud data fabric. And one of the big things that the Goldman person that wrote the piece and his name I forget right now, but is he pointed out that he could have it do some of the complex equities modeling for him, but it was at six times the cost. And so what I think a lot of that has to do with is the initial development of a model and training and bringing all the data together on a fabric that can be appreciated by a generative tool is going to be front-loaded expensive, so at six times or eight times, whatever it was.
But over time, once you’ve optimized that, there has to be a factory element to it as you spend big to build it. And then over time it starts to create lots of efficiency. And I don’t know that they’re weighing that in yet because right now it feels like it’s all build and there’s a continuous build because the data. But listen, 20 years of ML pipeline, Pat and everything else, we still haven’t gotten that multi-hybrid cloud data fabric to where it’s easy to use for a real looking enterprise data state and that’s going to slow down AI. We got to figure that out. It’s got to get figured out. I know there’s some things out there. Probably it’s something we should have a whole different show to talk about
Author Information
Daniel is the CEO of The Futurum Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise.
From the leading edge of AI to global technology policy, Daniel makes the connections between business, people and tech that are required for companies to benefit most from their technology investments. Daniel is a top 5 globally ranked industry analyst and his ideas are regularly cited or shared in television appearances by CNBC, Bloomberg, Wall Street Journal and hundreds of other sites around the world.
A 7x Best-Selling Author including his most recent book “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor.
An MBA and Former Graduate Adjunct Faculty, Daniel is an Austin Texas transplant after 40 years in Chicago. His speaking takes him around the world each year as he shares his vision of the role technology will play in our future.
