Tech Brew Ride Home - Fri. 07/23 – Alphabet’s New Moonshot Company: Intrinsic

Episode Date: July 23, 2021

Alphabet has a new moonshot company. Existing Big Bet DeepMind might have had a big breakthrough. Why Snap and Twitter are sharing an earnings narrative right now. Hint: it’s cause they’re growing again. And, of course, the Weekend Longreads Suggestions. Sponsors: CreditKarma.com/podcast SetApp.com Links: Google parent Alphabet launches Intrinsic: a new company to build software for industrial robots (The Verge) DeepMind creates ‘transformative’ map of human proteins drawn by artificial intelligence (The Verge) Twitter posts fastest revenue growth since 2014 in pandemic rebound (CNBC) Snap pops more than 16% on earnings beat and user growth (CNBC) Weekend Longreads Suggestions: What Ever Happened to IBM’s Watson? (NYTimes) Startup Claims Breakthrough in Long-Duration Batteries (WSJ) The Novel Material That’s Shrinking Phone Chargers, Powering Up Electric Cars, and Making 5G Possible (WSJ) Robotaxis: have Google and Amazon backed the wrong technology? (Financial Times) Learn more about your ad choices. Visit megaphone.fm/adchoices

On April 4th, 2023, around 2 in the morning, a man was found stabbed multiple times on a sidewalk in downtown San Francisco. Hey, who did this to you? What happened next turned the story into a political firestorm. Reports have identified the victim as Bob Lee, the founder of Cash App. From Bloomberg Podcasts, this is Foundering, the Killing of Bob Lee, beginning April 16. Welcome to the Tech meme right home for Friday, July 23rd, 2021. I'm Brian McCullough today. Alphabet has a new moonshot company, while existing Big Bet Deep Mind might have had a big breakthrough. Why Snap and Twitter are sharing an earnings narrative right now. Hint, it's because

they're growing again. And of course, the weekend long read suggestions. Here's what you miss today in the world of tech. Alphabet has a new moonshot. It's called Intrinsic, a new company to build apparently, although we're not entirely sure, software for industrial robots. And so Intrinsic will join Alphabet's portfolio of other bets. That includes the likes of Waymo, Wing, and Verily, quoting The Verge. Details on what exactly intrinsic is building or who its customers will be are unclear. A blog post from the company's new CEO, Wendy Tan White, discusses intrinsic's ambitions in broad terms, saying it will, quote, unlock the creative and economic potential of industrial robotics for millions more businesses, entrepreneurs, and developers,

end quote, by creating software that will make industrial robots, quote, easier to use, less costly and more flexible, end quote. Robotics have been an obsession at Google for years, but that companies' efforts have been unfocused and have yet to produce any commercial hits. In 2013, Google went on a shopping spree for robots, buying seven companies in roughly six months, including Shaft, a Japanese firm known for bipedal robots, botten dolly, makers of very cool viral videos, and Boston Dynamics, which needs no introduction. The effort was named Repliquant and headed by Andy Rubin,

an executive who co-founded the Android mobile operating system. Over the years, though, no news emerged from Replit, and Google either sold off or shut down most of its acquisitions. Why? Partly because robots are hard to make and not very profitable, but also because of Rubin's departure from the company in 2014, after being accused of sexual misconduct, which Google kept secret at the time. Since replicant's failure, the company has focused more on the software side of things, using machine learning to teach robots to manipulate objects without direct supervision.

This plays into Google's strengths and will apparently be intrinsic's focus going forward. Over the last few years, our team has been exploring how to give industrial robots the ability to sense, learn, and automatically make adjustments as they're completing tasks, so they work in a wider range of settings and applications. writes Tan White in the blog post. We've been testing software that uses techniques like automated perception, deep learning, reinforcement learning, motion planning, simulation, and force control, end quote. Speaking of another alphabet moonshot or other bet, alphabet subsidiary deep mind, says it used AI to create transformative mapping of human proteins. Some compare the potential

impact of this work to that of the original human genome project, which big if true, quoting the verge. Proteins are long, complex molecules that perform numerous tasks in the body from building tissue to fighting disease. Their purpose is dictated by their structure, which folds like origami into complex and irregular shapes. Understanding how a protein folds helps explain its function, which in turn helps scientists with a range of tasks from pursuing fundamental research on how the body works, to designing new medicines and treatments. Previously, determining the structure of a protein relied on expensive and time-consuming experiments. But last year, DeepMind showed it can produce accurate predictions of a protein structure using AI software called AlphaFold. Now the company is

releasing hundreds of thousands of predictions made by the program to the public. Quote, I see this as the culmination of the entire 10-year-plus lifetime of DeepMind. Company's CEO and co-founder Demise Hasebiz told The Verge, quote, from the beginning. This is a culmination. This is what we set out to do to make breakthroughs in AI, test that on games like Go and Atari, and apply that to real-world problems to see if we can accelerate scientific breakthroughs and use those to benefit humanity, end quote. There are currently around 180,000 protein structures available in the public domain, each produced by experimental methods and accessible through the protein data bank. Deep Mind is releasing predictions for the structure of some 350,000

proteins across 20 different organisms, including animals like mice and fruit flies and bacteria like E. coli. There is some overlap between deep minds data and pre-existing protein structures, but exactly how much is difficult to quantify because of the nature of the models. Most significantly, the release includes predictions for 98% of all human proteins, around 20,000 different structures, which are collectively known as the human proteome. It isn't the first public data set of human proteins, but it is the most comprehensive and accurate. If they want, scientists can download the entire human proteome for themselves, says AlphaFode's technical lead John Jumper. There's a human proteum. Dot zip effectively. I think it's about 50

gigabytes in size, Jumper tells the verge. You can put it on a flash drive if you want, though, it wouldn't do you much good without a computer for analysis, end quote. After launching this first tranche of data, deep mine plans to keep adding to the store of proteins, which will be maintained by Europe's flagship life sciences lab, the European Molecular Biology Laboratory, or EMBL. By the end of the year, DeepMind hoped to release predictions for 100 million protein structures, a dataset that will be, quote, transformative for our understanding of how life works, according to Edith Heard, Director General of the EMBL. The data will be free in perpetuity for both scientific and commercial researchers, says Hasebus. Quote, anyone can use it for anything,

the DeepMind CEO noted at a press briefing. They just need to credit the people. people involved in the citation, end quote. Understanding a protein structure is useful for scientists across a range of fields. The information can help design new medicines, synthesize novel enzymes that break down waste materials, and create crops that are resistant to viruses or extreme weather. Already, DeepMind's protein predictions are being used for medical research, including studying the workings of the virus that causes COVID-19. New data will speed these efforts, but scientists note it will still take a lot of time to turn this information into real-world results. Quote, I don't think it's going to be something that changes the way patients are

treated within the year, but it will definitely have a huge impact for the scientific community. Marcello C. Sousa, a professor at the University of Colorado's biochemistry department, told The Verge, end quote. Two super interesting earnings reports yesterday, Twitter and Snap. And it's weird. It's not only that Twitter and Snap happen to report on the same day, it's also that, increasingly, the narrative around both these companies is very similar to. It was within the lifetime of this podcast that both of these companies were seen as maybe becoming also Rans in the social networking game. They couldn't achieve the scale that Facebook had, nor could they monetize as well as other networks were doing. I mean, remember when

Snap was a sub-five dollar stock? They had that busted Android app and their user numbers were actually shrinking. And Twitter was laughed at for never having iterated on its product basically ever. Well, what a difference three years can make. Both stocks are flirting with all-time highs and are pleasing Wall Street with growth numbers like Twitter beating the streets expectations with Q2 revenue of $1.19 billion up 74% year over year, ad revenue of $1.05 billion up 87% year over year, and monetizable daily active users, remember that's Twitter's favorite metric, of 206 million, which was up 11% year over year. And Twitter gave good forward-looking guidance, quoting CNBC. With respect to guidance, Twitter said it sees $1.22 billion to $1.3 billion in third quarter revenue.

Analysts polled by Refinnative had expected $1.17 billion in revenue. For all of 2021, Twitter said that it expects headcount and total expenses to up at least 30%, and that revenue will grow faster than expenses, end quote. Snap, meanwhile, reported Q2 revenue of $982 million, up 116% year over year, Daily active users were up 23% year-over-year to 293 million, and its net loss shrunk 53% year-over-year to only $152 million. Snap is now growing more than it was the year that it IPOed. Twitter's revenue growth is the most it's seen since 2014. Snap was up as much as 23% in stock trading this morning, and Twitter up as much as 4%.

There's one more narrative both of these companies share, given GDPR, given Apple's app tracking changes to iOS, might both of these companies suddenly be more attractive to advertisers since their models for making money and their models for advertising rely less on tracking you around the web as opposed to just advertising to you inside their own apps? We might actually already be seeing this play out. For example, note that Snap's revenue more than doubled, quoting CNBC. Snap said the company was not impacted by Apple's iOS 14.5 privacy changes as it had anticipated that it would be. This was due to. to the mobile operating system update rolling out later than expected, iOS users being slow to

update their devices and Snap observing, quote, higher opt-in rates than we are seeing reported generally across the industry, which we believe is due in part to the trust our community has in our products and our business. Jeremy Gorman, Snap's chief business officer, said in her prepared remarks. This has given us more time with advertisers to navigate the transition, but also means the effects of these changes will come later than we initially expected, Gorman said, end quote. And as for Twitter, quote, the impact from changes in Apple's iOS 14.5 release associated with tracking were lower than expected, Twitter said, in its shareholder letter, end quote. Time for the weekend long read suggestions. We mentioned Deep Mind and its breakthrough on protein mapping earlier in the show. But what about one of its biggest competitors, Watson? Well, the New York Times takes a look at how Watson has maybe not been the breakthrough success.

that IBM was expecting it to be by now, quote, Watson wasn't just going to change industries, it was going to breathe new life into IBM, a giant company but one dependent on its legacy products. Inside IBM, Watson was thought of as a technology that could do for the company what the mainframe computer once did, provide an engine of growth and profits for years, even decades. Watson has not remade any industries, and it hasn't lifted IBM's fortunes. The company trails rivals that emerged as the leaders in cloud computing, AI, Amazon, Microsoft, and Google. While the shares of those three have multiplied in value many times, IBM's stock price is down more than 10% since Watson's Jeopardy Triumph in 2011. The company's

missteps with Watson began with its early emphasis on big and difficult initiatives, intended to generate both a claim and sizable revenue for the company, according to many of the more than a dozen current and former IBM managers and scientists interviewed for this article, end quote. But hey, let's stick with making this a day of breakthrough. news. The Wall Street Journal says a startup called Form Energy has seen a breakthrough in iron air batteries, which could have big ramifications for storing electricity on the power grid. Quote, Form is preparing to soon be in production of the kind of battery you need to fully retire thermal assets like coal and natural gas power plants, said the company's chief executive

Mateo Jeromilo, who developed Tesla's power wall battery and worked on some of its earliest automotive power trains. On a recent tour of Form's windowless laboratory, Mr. Jaramilo gestured to barrels filled with low-cost iron pellets as its key advantage in the rapidly evolving battery space. Its prototype battery nickname Big Jim is filled with 18,000 pebble-sized gray pieces of iron, an abundant, non-toxic, and non-flammable material. For a lithium ion battery cell, the workhorse of electric vehicles and today's grid-scale batteries, the nickel, cobalt, lithium, and Maganese minerals used currently

cost between $50 and $80 per kilowatt hour of storage, according to analysts. Using iron, form believes it will spend less than $6 per kilowatt hour of storage on materials for each cell. Packaging the cells together into a full battery system will raise the price to less than

$20 per kilowatt hour, a level at which academics have said, renewables plus storage, could fully replace traditional fossil fuel burning power plants, end quote. And how? And how about gallium? Once an industrial waste byproduct, that's shrinking phone chargers and leading to advances in electric cars, quoting the journal again. Present in most LED screens, as well as the LED lights that now provide much indoor illumination, is the metal gallium. And while not as well known as silicon, it is taking over in many of the places that silicon once reigned supreme, from antennas to charging bricks and other energy converting systems known as power electronics.

In the process, it's enabling a surprising array of new technologies from faster charging cell phones to lighter electric vehicles to more power-efficient data centers that run the services and apps we use. A byproduct of extracting aluminum from rock, gallium has such a low melting temperature that it turns into a runny, slippery white liquid when you hold it in your hand. On its own, it isn't terribly useful. Combine it with nitrogen to make gallium nitrate, and it becomes a hard crystal with valuable properties. It shows up in laser sensors used in many self-driving cars, antennas that enable today's fast cellular wireless networks, and increasingly in electronics critical to making renewable energy harvesting more efficient. Many of the most tangible things made possible by gallium nitrate, also known as GAN, are happening in power electronics. Today you can buy small USBC chargers with enough juice to power your laptop,

phone and tablet simultaneously, even though they are no bigger than the much less powerful versions that have four years come with our gadgets. Power electronics that convert one voltage level to another are also key to many aspects of electric vehicles. They are smaller, lighter, more efficient, and emit less heat so EVs can travel further on a charge, says Jim Whittem, chief executive of chipmaker GAN systems. Those properties also are great at squeezing significantly more electricity out of renewable energy sources such as solar panels, he adds. Even small efficiency gains in converting electricity add up when they happen multiple times, as in a renewable power grid that includes battery storage, end quote. I've said many, many times that

whoever cracks the battery nut will make billions, perhaps trillions of dollars, so maybe there's two angles to that. And finally, this week, I usually don't share stories from the Financial Times because they have such a hard paywall. But if you can get through the paywall, this is the story that I discussed on the Twitter space the other night. It asks the question, have all of these self-driving startups been going about self-driving the wrong way. Driverless groups such as Waymo, Microsoft-backed Cruise, Amazon-owned Zooks, and Aurora, which announced plans for a public listing last week, are betting on a moonshot solution with no plan B. They plan to offer full autonomy, albeit ring-fenced to certain locations,

or nothing at all. In regulatory jargon, this is called Level 4, in which a robot driver requires no input from passengers. Level 5, the highest step, would allow the vehicle to go anywhere. This go-big-or-go-home approach stands in direct opposition to the step-by-step path of the ADAS players led by suppliers Mobili, Aptiv, Magna, and Bosch, which work with all the major carmakers. Their advances mean most new vehicles already have partial automation, levels 1 and 2, including cruise control and automated braking. Tesla's autopilot system is the best-known level 2 system. The notion that this low-cost, evolutionary track could experience a butterfly-like transformation to offer a fully driverless experience

has long been dismissed by the level four groups. Chris Ermson, Aurora Chief Executive, put it eloquently in 2015 when he was Google's leading driverless engineer, quote, conventional wisdom would say that we'll just take these driver assistance systems and we'll kind of push them, and over time, they'll turn into self-driving cars, he said. Well, that's like me saying that if I work really hard at jumping one day, I'll be able to fly, end quote. Ermsum's logic felt sound at the time. ADAS was rudimentary, where robotaxies seemed just a couple of years away from mass deployment. Waymo prepared to order 82,000 such vehicles in 2018. Uber projected it would have 100,000 on the road by 2020, and Lyft divined that a majority of its rides would be autonomous by 2021. But none of that happened. Instead, the closer they got to consumer-facing products, the more complex the problem was understood to be.

At the same time, the traditional automotive industry has been galvanized by these efforts and has evolved ADAS into a multifaceted feature set capable of hands-free highway driving, automated lane changes, and robotic valet parking. Iignma says the dramatic improvements in ADAS were unforeseen, and he now sees the two technology curves converging. Level four groups are desperately trying to bring costs down to boost their business case, while ADAS suppliers are accelerating their performance to achieve maximum safety. Quote, in 2015, I would have agreed with Chris Ermson. Eignema says, every intelligent observer in the industry believed that was the right path forward. But what that failed to anticipate was the increase in performance, in part enabled by deep learning and other advances that would allow us to do things with radars and cameras that I would not have thought possible in 2015, end quote. I've said it before, and I'll say it again, again. I don't need level five or even level four.

If I can just read a book while commuting on the highway to work, then that's all I really need. I can take over the wheel when I get off the on-ramp and need to go into more complicated city streets. No worries for me at all if I can just bring an entire season of a Netflix show and binge on it as I drive the family down I-95 to visit Grandma and Grandpa for the holidays. That's the transformative technology that I really care about. Whether there's a person or a robot driving me when I need a taxi or a burrito, is delivered to me is neither here nor there, if I'm being honest. It's more a question of expense to the companies and not to me. All right, there is no additional Ride Home Plus content this weekend, but I will share the Twitter space. We did this Wednesday night with everybody tomorrow.

Talk to you on Monday.