Custom Silicon and Start-ups

In our last two posts, we outlined what we see as an important shift in the semis industry. More customers want more customized chips, and the slowing of Moore’s Law has opened the door (and shoved everyone through it) to make this economically viable. Last week, we pointed out that this trend is both a threat and an opportunity for the large, incumbent chip makers. Here we want to explore what this means for new chip companies.

At the most basic level, we are seeing companies shift from buying general purpose chips to buying more tailored systems on a chip (SoC). Instead of buying two chips – a discrete GPU and a discrete CPU – they might buy a single SoC that contains both a CPU and a GPU and maybe a few other functions. The best known example of this is Apple’s M Series CPU which has both of those plus a bunch of AI accelerators and a few other blocks. This makes sense for the customer, but it turns out to be a really challenging problem for the vendors. Chip companies have to employ large teams of designers and other engineers. This is high skilled labor and their costs add up. There are also large up-front costs for licenses for things like EDA tools. And then there are tape-out costs, upfront payments to the foundry to begin production which start in the tens of millions of dollars for advanced nodes. The advantage of catalog, general purpose chips is that they offer maximum leverage on these fixed costs. Design a successful chip, and then move the team on to the next generation while racking up healthy contribution margins from each chip sale.

By contrast, custom chips are very risky because sales are entirely dependent on getting that one chip right. Every customer wants their own chip, but that evaporates the operational leverage of the model. Tape out costs alone doom custom parts for most customers. The worst case occurs when the chip company designs an SoC with the wrong mix of sub-systems, and no one buys it; the chip company is out all that money.

This problem has become very pronounced in the seemingly hot category for AI accelerators. Five years ago, VCs poured money into the space into a few dozen companies making these chips. And so far, almost none of those companies have generated significant revenue (although a few had some very good exits). The problem is that they thought they could build general purpose accelerators when it turned out customers wanted something much more specific to their individual needs.

That bring said, the shift away from general compute has cracked open the door, essentially fragmenting a once largely monolithic industry. Tailored solutions of SoCs by definition will create niche opportunities which should provide plenty of toeholds for smaller companies to enter the fray. Everyone wants Tesla and GM as a customer, but how do Rivian and Nikola get the big chip companies to return their calls?

There are a few approaches start-ups can take to squaring this circle.

EdgeQ is a good example. They are building a chip for 5G networks. This field was dominated by Texas Instruments, Ericsson, NXP and Nokia for years. But the new wireless standard is, if nothing else, a giant welcome sign for new entrants to the market. This process is further aided by the Open RAN project, which is brining new hardware makers into the business. By building a chip around the 5G standard, EdgeQ has created a chip that theoretically may be of great interest to emerging hardware vendors in the space. Not so long ago, anyone entering the market for wireless hardware would have just turned to Intel (who is not surprisingly a big proponent of Open RAN), but the industry will clearly benefit from something more customized to the workloads. EdgeQ does not have to build a different chip for each customer, but can build a solution tailored to the standards and build on from that beach head.

Another example is Indie Semiconductor. Indie is probably best known for its eye-popping SPAC fundraising, but they will eventually be better known for their specialization in the automotive semis segment. Selling chips to auto makers is painful. Product cycles are, by semis standards, ridiculously long – often five to seven years, or longer. The incumbent auto makers are all large companies with very demanding purchase standards as well as some grueling specifications and qualifications (data center CPUs do not need to contend with high external temperatures, humidity and constant vibration). Indie has essentially built its model around handling all of that. Most importantly, they have a process in place for designing chips that customers feel are customized to them, but are sufficiently interchangeable that Indie does not have to re-invent the wheel for each customer. Indie is a bit different in that most of the parts they make are at trailing edge processes and thus not subject to the vagaries of Moore’s Law. However, the company clearly has ambitions to move in further up the stack. Their work in the unglamorous parts of auto semis lets them build relationships with the big customers and thus win themselves a seat at the table for conversations around those more advanced chips.

These are just two ways that start-ups can benefit from the shift in the market, there are many other paths. That being said, both examples highlight important common threads. Both have chosen to go after specific industries, their web sites do not have dozens of industry use cases listed. Both are also focused on specific outside frames of reference – auto qualifications for Indie, wireless standards for EdgeQ. We would generalize more broadly to say companies should focus on specific software stacks – not exactly true in Indie’s case yet, but very true for EdqeQ (wireless standards are just a very peculiar form of software). There are many other outside frames upon which start-ups can hang their hats.

As we have mentioned often in the past, US Venture investors have been generally avoiding semis for a decade. The shift in compute trends greatly alters the return calculations these investors need to make when assessing potential outcomes. And this should open the door to funding for many more chip and system start-ups.

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