Intel buying Mobileye for up to $16B to expand in self-driving tech
techcrunch.com
techcrunch.com
Thus it is a strategic move on Intel's part to fend off competitors rather than reflective of the intrinsic value of Mobileye.
BTW what was Mobileye's revenue last year and profit margin? About $350M in 2016, with probably $500M in 2017 it seems. So the multiple is around 30x revenue or so?
Talking about PE and multiples is pointless for tech companies where synergies and rapid adoption/changes are common.
Intrinsic value usually refers to the present (discounted) value of future earnings.
>There is price and price ($16B) is determined by the market.
How is it determined if all valuation is supposed to be pointless?
>Talking about PE and multiples is pointless for tech companies where synergies and rapid adoption/changes are common
For a public company that has existed for almost two decades it absolutely makes sense to consider revenue multiples among other factors.
It may well be that the value of the company in Intel's hands is worth more than it is worth for other, non-strategic, investors. I agree that there is a lot of potential variability in tech, but that doesn't mean any fantasy price is right just because some people buy some shares at that price (which is what market prices mean)
"Intrinsic value" is a basic financial term that is widely used and has a well defined meaning - just type the term into Google: https://en.wikipedia.org/wiki/Intrinsic_value_(finance)
The companies are a lot more linked than it seems.
This is probably not too bad a spot to be in, at least until fully autonomous vehicles have become mainstream. They seem to be profitable, at least.
$16B for Mobilieye as a route to market (they already have the relationships and supply chains set up with car manufacturing) sounds like a lot but Intel needs a fast track if they want to compete with Nvidia (and ARM and Qualcomm) in that space.
Furthermore, I'm guessing x86 has almost no representation in the self-driving car space at the moment. They're probably hoping to change that.
I completely agree.
>> Furthermore, I'm guessing x86 has almost no representation in the self-driving car space at the moment. They're probably hoping to change that.
But this, not so much. x86 is way too power hungry (especially for EVs) and way too expensive for automotive use.
it isn't a power or efficiency problem. it's a margin problem. vehicle electronics have margins that consumer devices don't. just look at the price of 95% useless in-car satnav.
When you're running a electric motor that pulls power on the magnitude of 1 * 10^5 W (i.e. 100 kW+) I doubt you care about a few extra watts total power load if you have an inefficient processor. Similarly for conventional fuel, an extra few watts on the load is hardly going to worry the alternator.
Sure an EV can suck 100kW or more of power, but only for a short time. And it can be put back into the battery via regenerative baking. Range is incredibly sensitive to electrical loads.
The reason that ARM processors are able to take so much less power than Intel is because their single threaded performance is much lower. As single threaded performance increases linearly the power required goes up as the square of that for architectural improvements and as the cube for frequency improvements modulo FO4 delays.
Intel's Atom processors haven't gotten huge amounts of love from the parent company but for DSPish code of the sort that cars are mostly running they should perform comparably to the equivalent ARM options.
I can get an off-the-shelf Xeon-D 8-core processor that runs at 35W and any single core would STOMP every ARM chip on the market. If I were to build that chip specifically for a car platform my power envelope would drop accordingly.
https://ark.intel.com/products/family/87041/Intel-Xeon-Proce...
This is an embedded application... not a gaming computer. If I move to Atom - which is what would likely be used for this sort of thing, you're talking less than 5W.
https://en.wikipedia.org/wiki/List_of_Intel_Atom_microproces...
Correct. But Atom processors performance are no better than the competition and don't currently have any of the common automotive peripherals (CAN for example).
Regardless, you're missing the point. Intel has the means to get into the space and create appropriate CPUs to compete. This acquisition makes it clear they're planning on doing just that.
simplest way, think of robots used to automate cleaning everything from the mall, your house, to the sides of the roads. or one day pulling up to a fueling facility and it automatically connects to your car for gas/electric/etc all is improved by better sensors and such
BMWs and other high end cars have had Mobileye as OEM for a long time, but the company itself is a bit of a legacy company and not always run well (and is based in Jerusalem which is even more legacy) - but like many Israeli tech stories has great tech.
http://www.prnewswire.com/news-releases/mobileye-completes-i...
It actually probably saved me from a minor accident on my first drive in my brand new car, getting it out of the dealership: It was raining heavily and visibility was crap, and I was a bit distracted finding all the controls and looking for the back window wipers (turns out there aren't any!). And I didn't notice the cars ahead of me stopped. The alarm went off and I hit the brakes (it was very low speed), and everything was fine.
If it would've been so easy, they would've done it with Atom in the mobile market. But it wasn't. Intel was losing $1 billion a quarter in mobile just to be competitive on price.
Intel absolutely lacks the cost structure to compete with Qualcomm's ARM chips, and that has already been proven. It's not a theory.
As for Ryzen, they can lower prices, but not by as much as you may think. Lowering prices is directly proportional with how many people Intel will have to fire to accommodate for a slightly lower cost structure that's more competitive with AMD.
For every 10% average reduction in price, Intel may have to fire at least a few thousand employees (across divisions, but more likely by gutting some non-profitable research projects, in the beginning).
However, those layoffs will also look bad on Intel's public image, so don't expect Intel to lower prices strategically across product lines to compete against AMD without serious consideration. But I really don't expect them to lower their average price point by more than 10% for the next few years, until Intel comes out with a more "streamlined" (fewer features) microarchitecture, that's more cost-effective to build.
The whole 3 ring circus of chipmakers, OEM's, and various component suppliers that stand to benefit from Autonomous vehicles is held aloft by a single tentpole that doesn't actually exist yet. It's just a twinkle in the eye of some AI genius who may very well still be an undergrad at the moment. Intel just spent 15 gigabucks assuaging their fear of missing out.
The field of AI and deep learning in particular is changing and progressing so fast that the experts of yesteryear are almost certainly not the people who will build the autonomous OS of the future. There will be a lot of misspent capital between now and the first safe, reliable, market ready, publicly accessible fully autonomous vehicle.
>the experts of yesteryear are almost certainly not the people who will build the autonomous OS of the future
is because it will be a very long time before we have anything like a Level 4 vehicle?
Drive.ai is an autonomous driving startup that's made up of mostly unknown Stanford AI lab labmates who dropped out of their PHD programs to build an autonomous OS, and what they're doing is so much more futuristic than what anybody else is doing. They've made more progress in less time with fewer resources than any of the big players. They've got 4 test vehicles, a team of 40 people, they're running on $12 million in venture capital, and they've demoed capabilities that the multi-billion dollar players don't have. They're just pure deep learning guys, they could have gone into fintech or NLP but they went for AVs starting with a blank slate and an abundance of unproven talent.
They're still behind Waymo and Cruise, but they're progressing at a higher rate of speed. Everybody in this game is subject to disruption from some nobody coming out of nowhere. Something like transfer learning drops out of the sky, it has the potential to totally revolutionize the way one might think about an Autonomous driving stack, and it all comes down to the genius who figures out how to apply it effectively. That genius could be anyone, no amount of money you spend can buy certainty in this race. Which makes it really fun to watch.
>I don't believe we're headed into any kind of AI trough.
Why? AI winter is a well-known phenomenon, AI hype has permeated tech, now business and is starting to push into the layman's consciousness. Does it not seem that a bust is near? The laymans perception of autonomous driving is a magic box that will drive them around while they read their phones and that it will be here in 5/10 years. I think that's just unsustainable. A car which can handle northern snow, midwestern winds, country potholes, city traffic, unpredictiable/aggressive drivers and which can do that with a lower accident rate than humans is our generations cold fusion. Fundamental breakthroughs are needed.
What strikes me is that we think because we can describe "driving" in one word, we think it is a specific task, but it seems much more general and AI developments on general learning are notoriously fraught. Your thoughts?
Any way you look at the autonomous driving problem it's a hard problem, but every few days it seems there's some paper coming out that demos a new optimization to one aspect or another of the autonomous vehicle development pipeline.
The world of modular deep learning systems, where you have various parent and child subsystems that can be quickly trained and swapped out is very much an open and field of research and my bet is on agile teams that can build and test models faster, and can take things from research to implementation in less time than the competition.
Drive.ai's best trade secret is the system they have for vastly reducing the amount of training data they need to get a result, and vastly reducing the amount of human labour needed to annotate or clean up said training data.
I don't know what the hype is. People are expecting terminator robots or something, that's not going to happen anytime soon. But progress in Machine learning has been steady and driving for a decade and shows know signs of letting up in the forseeable future, because we just keep opening up new frontiers to explore. There's so much to do.
But that is different to another AI winter. AI is making real companies real money this time.
dude needs to get back to hacking iphones it seems.
"It's been a bear to get done, but prob 10 days or so, depending on full speed autosteer test results" https://twitter.com/elonmusk/status/841041891747545089
But Mobileye isn't sitting still, so if the relationship hadn't been terminated, Tesla would've been stuck with whatever Mobileye's latest and greatest offering might be.
What's interesting is that if you compare the HW2 sensor suite to Mobileye's next-gen sensor plans, they are very similar, almost the same. They were both working on something together before the relationship went sour.
Musk hinted recently that 1 PX2 is not enough, and that 2 may be necessary for L4. There's certainly no consensus as to how much compute is needed, the more the better, but I'm skeptical that the hardware costs will be low enough near term to justify putting it in privately owned autonomous cars. I think Tesla has made costly strategic errors in the Autonomy department, and that Musk in particular has repeatedly underestimated the challenge of developing a fully autonomous vehicle. I don't think he's making that mistake anymore.
You couldn't train a good autonomous driving agent even if you used a massive GPU cluster.
I'm not saying better hardware doesn't help, it definitely helps incrementally but it's not going to be enough to solve this problem.
However I'd wager to say that betting on a powerful Nvidia GPU/chipset (piggybacking on general ML/CUDA ecosystem progress) to be able process rapidly advancing autonomous driving algorithms is a more future proof bet for Tesla than relying on already outdated hardware/algorithms from Mobileye.
The truth is, Tesla vehicles are safer than their counterparts in almost every situation imaginable. Mobileye screwed the pooch when they began issuing negative press releases that attempted to push all the responsibility and potential liability onto Tesla.
Intel is smarter than that. Intel has become fairly accustomed to implementing and following through with aggressive development and launch cycles.