Europe plans a Chips Act to boost semiconductor sovereignty

The EU will use legislation to push for greater resilience and sovereignty in regional semiconductor supply chains.

The bloc’s president trailed a forthcoming ‘European Chips Act’ in a state of the union speech today. Ursula von der Leyen suggested that gaining greater autonomy in chipmaking is now a key component of the EU’s overarching digital strategy.

She flagged the global shortage of semiconductors, which has led to slow downs in production for a range of products that rely on chips to drive data processing — from cars and trains to smartphones and other consumer electronics — as driving EU lawmakers’ concern about European capacity in this area.

“There is no digital without chips,” said von der Leyen. “While we speak, whole production lines are already working at reduced speed — despite growing demand — because of a shortage of semi-conductors.

“But while global demand has exploded, Europe’s share across the entire value chain, from design to manufacturing capacity has shrunk. We depend on state-of-the-art chips manufactured in Asia. So this is not just a matter of our competitiveness. This is also a matter of tech sovereignty. So let’s put all of our focus on it.”

The Chips Act will aim to link together the EU’s semiconductor research, design and testing capacities, she said, calling for “coordination” between EU and national investments in this area to help boost the bloc’s self-sufficiency.

“The aim is to jointly create a state-of-the-art European chip ecosystem, including production. That ensures our security of supply and will develop new markets for ground-breaking European tech,” she added.

The EU president couched the ambition for bolstering European chip capacity as a “daunting task” but likened the mission to what the bloc did with its Galileo satellite navigation system two decades ago.

“Today European satellites provide the navigation system for more than 2 billion smartphones worldwide. We are world leaders. So let’s be bold again, this time with semi-conductors.”

In follow up remarks, the EU’s internal market commissioner, Thierry Breton, put a little more meat on the bones of the legislative plan — saying the Commission wants to integrate Member State efforts into a “coherent” pan-EU semiconductor strategy and also create a framework “to avoid a race to national public subsidies fragmenting the single market”.

The aim will be to “set conditions to protect European interests and place Europe firmly in the global geopolitical landscape”, he added.

Per Breton, the Chip Act will comprise three elements: Firstly, a semiconductor research strategy that will aim to build on work being done by institutions such as IMEC in Belgium, LETI/CEA in France and Fraunhofer in Germany.

“Building on the existing research partnership (the KDT Joint Undertaking), we need to up our game, and design a strategy to push the research ambitions of Europe to the next level while preserving our strategic interests,” he noted.

The second component will consist of a collective plan to boost European chipmaking capacity.

He said the planned legislation will aim to support chip supply chain monitoring and resilience across design, production, packaging, equipment and suppliers (e.g. producers of wafers).

The goal will be to support the development of European “mega fabs” that are able to produce high volumes of the most advanced (towards 2nm and below) and energy-efficient semiconductors.

However the EU isn’t planning for a future when it can make all the chips it needs itself.

The last plank of the European Chip Act will set out a framework for international co-operation and partnership.

“The idea is not to produce everything on our own here in Europe. In addition to making our local production more resilient, we need to design a strategy to diversify our supply chains in order to decrease over-dependence on a single country or region,” Breton went on. “And while the EU aims to remain the top global destination of foreign investment and we welcome foreign investment to help increase our production capacity especially in high-end technology, through the European Chips Act we will also put the right conditions in place to preserve Europe’s security of supply.”

“The US are now discussing a massive investment under the American Chips Act designed to finance the creation of an American research centre and to help open up advanced production factories. The objective is clear: to increase the resilience of US semiconductor supply chains,” he added.

“Taiwan is positioning itself to ensure its primacy on semiconductor manufacturing. China, too, is trying to close the technological gap as it is constrained by export control rules to avoid technological transfers. Europe cannot and will not lag behind.”

In additional documentation released today, the EU said the Chips Act will build on other digital initiatives already presented by the Von der Leyen Commission — such as moves to contain the power of “gatekeeper” Internet giants and increase platforms’ accountability (the Digital Markets Act and Digital Services Act); regulate high risk applications of AI (the Artificial Intelligence Act); tackle online disinformation (via a beefed up code of practice); and boost investment in regional digital infrastructure and skills.

6 tips for establishing your startup’s global supply chain

Startups are hard work, but the complexities of global supply chains can make running hardware companies especially difficult. Instead of existing within a codebase behind a screen, the key components of your hardware product can be scattered around the world, subject to the volatility of the global economy.

I’ve spent most of my career establishing global supply chains, setting up manufacturing lines for 3D printers, electric bicycles and home fitness equipment on the ground in Mexico, Hungary, Taiwan and China. I’ve learned the hard way that Murphy’s law is a constant companion in the hardware business.

But after more than a decade of work on three different continents, there are a few lessons I’ve learned that will help you avoid unnecessary mistakes.

Expect cost fluctuations, especially in currency and shipping

Shipping physical products is quite different from “shipping” code — you have to pay a considerable amount of money to transport products around the world. Of course, shipping costs become a line item like any other as they get baked into the overall business plan. The issue is that those costs can change monthly — sometimes drastically.

At this time last year, a shipping container from China cost $3,300. Today, it’s almost $18,000 — a more than fivefold increase in 12 months. It’s safe to assume that most 2020 business plans did not account for such a cost increase for a key line item.

Shipping a buggy hardware product can be exponentially costlier than shipping buggy software. Recalls, angry customers, return shipping and other issues can become existential problems.

Similar issues also arise with currency exchange rates. Contract manufacturers often allow you to maintain cost agreements for any fluctuations below 5%, but the dollar has dropped much more than 5% against the yuan compared to a year ago, and hardware companies have been forced to renegotiate their manufacturing contracts.

As exchange rates become less favorable and shipping costs increase, you have two options: Operate with lower margins, or pass along the cost to the end customer. Neither choice is ideal, but both are better than going bankrupt.

The takeaway is that when you set up your business, you need to prepare for these possibilities. That means operating with enough margin to handle increased costs, or with the confidence that your end customer will be able to handle a higher price.

Overorder critical parts

Over the past year, many businesses have lost billions of dollars in market value because they didn’t order enough semiconductors. As the owner of a hardware company, you will encounter similar risks.

The supply for certain components, like computer chips, can be limited, and shortages can arise quickly if demand increases or supply chains get disrupted. It’s your job to analyze potential choke points in your supply chain and create redundancies around them.

Top four highlights of Elon Musk’s Tesla AI Day

Elon Musk wants Tesla to be seen as “much more than an electric car company.” On Thursday’s Tesla AI Day, the CEO described Tesla as a company with “deep AI activity in hardware on the inference level and on the training level” that can be used down the line for applications beyond self-driving cars, including a humanoid robot that Tesla is apparently building.

Tesla AI Day, which started after a rousing 45 minutes of industrial music pulled straight from “The Matrix” soundtrack, featured a series of Tesla engineers explaining various Tesla tech with the clear goal of recruiting the best and brightest to join Tesla’s vision and AI team and help the company go to autonomy and beyond.

“There’s a tremendous amount of work to make it work and that’s why we need talented people to join and solve the problem,” said Musk.

Like both “Battery Day” and “Autonomy Day,” the event on Thursday was streamed live on Tesla’s YouTube channel. There was a lot of super technical jargon, but here are the top four highlights of the day.

Tesla Bot: A definitely real humanoid robot

This bit of news was the last update to come out of AI Day before audience questions began, but it’s certainly the most interesting. After the Tesla engineers and executives talked about computer vision, the Dojo supercomputer and the Tesla chip (all of which we’ll get to in a moment), there was a brief interlude where what appeared to be an alien go-go dancer appeared on the stage, dressed in a white body suit with a shiny black mask as a face. Turns out, this wasn’t just a Tesla stunt, but rather an intro to the Tesla Bot, a humanoid robot that Tesla is actually building.

Image Credits: Tesla

When Tesla talks about using its advanced technology in applications outside of cars, we didn’t think he was talking about robot slaves. That’s not an exaggeration. CEO Elon Musk envisions a world in which the human drudgery like grocery shopping, “the work that people least like to do,” can be taken over by humanoid robots like the Tesla Bot. The bot is 5’8″, 125 pounds, can deadlift 150 pounds, walk at 5 miles per hour and has a screen for a head that displays important information.

“It’s intended to be friendly, of course, and navigate a world built for humans,” said Musk. “We’re setting it such that at a mechanical and physical level, you can run away from it and most likely overpower it.”

Because everyone is definitely afraid of getting beat up by a robot that’s truly had enough, right?

The bot, a prototype of which is expected for next year, is being proposed as a non-automotive robotic use case for the company’s work on neural networks and its Dojo advanced supercomputer. Musk did not share whether the Tesla Bot would be able to dance.

Unveiling of the chip to train Dojo

Image Credits: Tesla

Tesla director Ganesh Venkataramanan unveiled Tesla’s computer chip, designed and built entirely in-house, that the company is using to run its supercomputer, Dojo. Much of Tesla’s AI architecture is dependent on Dojo, the neural network training computer that Musk says will be able to process vast amounts of camera imaging data four times faster than other computing systems. The idea is that the Dojo-trained AI software will be pushed out to Tesla customers via over-the-air updates. 

The chip that Tesla revealed on Thursday is called “D1,” and it contains a 7 nm technology. Venkataramanan proudly held up the chip that he said has GPU-level compute with CPU connectivity and twice the I/O bandwidth of “the state of the art networking switch chips that are out there today and are supposed to be the gold standards.” He walked through the technicalities of the chip, explaining that Tesla wanted to own as much of its tech stack as possible to avoid any bottlenecks. Tesla introduced a next-gen computer chip last year, produced by Samsung, but it has not quite been able to escape the global chip shortage that has rocked the auto industry for months. To survive the shortage, Musk said during an earnings call this summer that the company had been forced to rewrite some vehicle software after having to substitute in alternate chips. 

Aside from limited availability, the overall goal of taking the chip production in-house is to increase bandwidth and decrease latencies for better AI performance.

“We can do compute and data transfers simultaneously, and our custom ISA, which is the instruction set architecture, is fully optimized for machine learning workloads,” said Venkataramanan at AI Day. “This is a pure machine learning machine.”

Venkataramanan also revealed a “training tile” that integrates multiple chips to get higher bandwidth and an incredible computing power of 9 petaflops per tile and 36 terabytes per second of bandwidth. Together, the training tiles compose the Dojo supercomputer. 

To Full Self-Driving and beyond

Many of the speakers at the AI Day event noted that Dojo will not just be a tech for Tesla’s “Full Self-Driving” (FSD) system, it’s definitely impressive advanced driver assistance system that’s also definitely not yet fully self-driving or autonomous. The powerful supercomputer is built with multiple aspects, such as the simulation architecture, that the company hopes to expand to be universal and even open up to other automakers and tech companies.

“This is not intended to be just limited to Tesla cars,” said Musk. “Those of you who’ve seen the full self-driving beta can appreciate the rate at which the Tesla neural net is learning to drive. And this is a particular application of AI, but I think there’s more applications down the road that will make sense.”

Musk said Dojo is expected to be operational next year, at which point we can expect talk about how this tech can be applied to many other use cases.

Solving computer vision problems

During AI Day, Tesla backed its vision-based approach to autonomy yet again, an approach that uses neural networks to ideally allow the car to function anywhere on earth via its “Autopilot” system. Tesla’s head of AI, Andrej Karpathy, described Tesla’s architecture as “building an animal from the ground up” that moves around, senses its environment and acts intelligently and autonomously based on what it sees.

Andrej Karpathy, head of AI at Tesla, explaining how Tesla manages data to achieve computer vision-based semi-autonomous driving. Image Credits: Tesla

“So we are building of course all of the mechanical components of the body, the nervous system, which has all the electrical components, and for our purposes, the brain of the autopilot, and specifically for this section the synthetic visual cortex,” he said.

Karpathy illustrated how Tesla’s neural networks have developed over time, and how now, the visual cortex of the car, which is essentially the first part of the car’s “brain” that processes visual information, is designed in tandem with the broader neural network architecture so that information flows into the system more intelligently.  

The two main problems that Tesla is working on solving with its computer vision architecture are temporary occlusions (like cars at a busy intersection blocking Autopilot’s view of the road beyond) and signs or markings that appear earlier in the road (like if a sign 100 meters back says the lanes will merge, the computer once upon a time had trouble remembering that by the time it made it to the merge lanes).

To solve for this, Tesla engineers fell back on a spatial recurring network video module, wherein different aspects of the module keep track of different aspects of the road and form a space-based and time-based queue, both of which create a cache of data that the model can refer back to when trying to make predictions about the road.

The company flexed its over 1,000-person manual data labeling team and walked the audience through how Tesla auto-labels certain clips, many of which are pulled from Tesla’s fleet on the road, in order to be able to label at scale. With all of this real-world info, the AI team then uses incredible simulation, creating “a video game with Autopilot as the player.” The simulations help particularly with data that’s difficult to source or label, or if it’s in a closed loop.

Background on Tesla’s FSD

At around minute forty in the waiting room, the dubstep music was joined by a video loop showing Tesla’s FSD system with the hand of a seemingly alert driver just grazing the steering wheel, no doubt a legal requirement for the video after investigations into Tesla’s claims about the capabilities of its definitely not autonomous advanced driver assistance system, Autopilot. The National Highway Transportation and Safety Administration earlier this week said they would open a preliminary investigation into Autopilot following 11 incidents in which a Tesla crashed into parked emergency vehicles. 

A few days later, two U.S. Democratic senators called on the Federal Trade Commission to investigate Tesla’s marketing and communication claims around Autopilot and the “Full Self-Driving” capabilities. 

Tesla released the beta 9 version of Full Self-Driving to much fanfare in July, rolling out the full suite of features to a few thousand drivers. But if Tesla wants to keep this feature in its cars, it’ll need to get its tech up to a higher standard. That’s where Tesla AI Day comes in. 

“We basically want to encourage anyone who is interested in solving real-world AI problems at either the hardware or the software level to join Tesla, or consider joining Tesla,” said Musk.

And with technical nuggets as in-depth as the ones featured on Thursday plus a bumping electronic soundtrack, what red-blooded AI engineer wouldn’t be frothing at the mouth to join the Tesla crew?

You can watch the whole thing here: 

Motivo raises $12M Series A to speed up chip design with AI

Chip design is a long slog of trial and error, taking years to bring a design to market. Motivo, a five year old startup from a chip industry veteran is creating software to speed up chip design from years to months using AI. Today the company announced a $12 million Series A.

Intel Capital led the round along with new investors Storm Ventures and Seraph Group, as well as participation from Inventus Capital. The company reports it has now raised a total of $20 million with its previous seed funding.

Motivo co-founder and CEO Bharath Rangarajan has worked in the chip industry for 30 years, and he saw a few fundamental trends and issues. For starters, the chip design process is highly time-intensive, taking years to come up with a successful candidate, and typically the first to market wins.

What’s more, Moore’s Law where you fit more and more electronics onto an increasingly powerful chip increases the complexity of these designs, and once in production, there is a lot of waste producing them. Rangarajan started the company to put artificial intelligence to work on the design process and bring chips to market faster with more accuracy in the production cycle.

“We can train an AI engine to bring about human judgment, and do a lot of design for manufacturability on the design without causing any other issue. So we avoid all these iteration loops [and we can also] design code and validation and timing and again we’re going from weeks and months to days,” he said.

The company’s ultimate goal is to take the chip design process and distill it down using software and intelligence from three years to three months, and while they are not there yet, they have started to attack the problem, and have a working product that looks at chip layout, the underlying RTL code that runs the chip and the netlist, which describes how the various pieces and electronics on the chip connect together.

One other differentiator is that the company is trying to make its AI transparent to explain why it made the decisions it did. “A lot of AI is just a black box. I don’t know why the self-driving car suddenly decided to swerve here. Our AI is understandable. We built the solution so that we can tell you why the AI is saying change the chip this way, or why it’s saying change it that way,” Rangarajan explained.

The company has paying customers. Although it can’t name them, there is probably a limited market for this kind of software, so you could make an educated guess that it’s the chip companies, especially with Intel Capital a lead investor on this round. At this point, the company has 15 employees, 12 of them being full time with plans to double or even triple over the next year, depending on how things go.

Hiring is always challenging for a company with a specific engineering focus like this one, but Rangarajan says that the team is already fairly diverse, and he is definitely looking at keeping that going as he builds the company. “We have to find the right people to join the company and you’re looking for any and all sorts of great people or backgrounds. […] In fact, the more the merrier as far as we’re concerned. We’ve got very experienced people who’ve grown up in the industry and we’ve still built up a fairly diverse team here,” he said.

For now, he plans to keep the office hybrid where people who want to come in can come in, but people who don’t want to like those with younger kids who aren’t vaccinated yet, can continue to work from home, he said. And that flexibility should continue even after offices open more completely.

China roundup: Keep down internet upstarts, cultivate hard tech

Hello and welcome back to TechCrunch’s China roundup, a digest of recent events shaping the Chinese tech landscape and what they mean to people in the rest of the world.

The tech industry in China has had quite a turbulent week. The government is upending its $100 billion private education sector, wiping billions from the market cap of the industry’s most lucrative players. Meanwhile, the assault on Chinese internet giants continued. Tech stocks tumbled after Tencent suspended user registration, sparking fears over who will be the next target of Beijing’s wrath.

Incisive observers point out that the new wave of stringent regulations against China’s internet and education firms has long been on Beijing’s agenda and there’s nothing surprising. Indeed, the central government has been unabashed about its desires to boost manufacturing and contain the unchecked powers of its service industry, which can include everything from internet platforms, film studios to after-school centers.

A few weeks ago I had an informative conversation with a Chinese venture capitalist who has been investing in industrial robots for over a decade, so I’m including it in this issue as it provides useful context for what’s going on in the consumer tech industry this week.

Automate the factories

China is putting robots into factories at an aggressive pace. Huang He, a partner at Northern Light Venture Capital, sees three forces spurring the demand for industrial robots — particularly ones that are made in China.

Over the years, Beijing has advocated for “localization” in a broad range of technology sectors, from enterprise software to production line automation. One may start to see Chinese robots that can rival those of Schneider and Panasonic a few years down the road. CRP, an NLVC-backed industrial robot maker, is already selling across Southeast Asia, Russia and East Europe.

On top of tech localization, it’s also well acknowledged that China is facing a severe demographic crisis. The labor shortage in its manufacturing sector is further compounded by the reluctance of young people to do menial factory work. Factory robots could offer a hand.

“Youngsters these days would rather become food delivery riders than work in a factory. The work that robots replace is the low-skilled type, and those that still can’t be taken up by robots pay well and come with great benefits,” Huang observed.

Large corporations in China still lean toward imported robots due to the products’ proven stability. The problem is that imported robots are not only expensive but also selective about their users.

“Companies need to have deep technical capabilities to be able to operate these [Western] robots, but such companies are rare in China,” said Huang, adding that the overwhelming majority of Chinese enterprises are small and medium size.

With the exceptions of the automotive and semiconductor industries, which still largely rely on sophisticated, imported robots, affordable, easy-to-use Chinese robots can already meet most of the local demand for industrial automation, Huang said.

China currently uses nearly one million six-axis robots a year but only manufactures 20% of them itself. The gap, coupled with a national plan for localization, has led to a frenzy of investments in industrial robotics startups.

The rush isn’t necessarily a good thing, said Huang. “There’s this bizarre phenomenon in China, where the most funded and valuable industrial robotic firms are generating less than 30 million yuan in annual revenue and not really heard of by real users in the industry.”

“This isn’t an industry where giants can be created by burning through cash. It’s not the internet sector.”

Small-and-medium-size businesses are happily welcoming robots onto factory floors. Take welding for example. An average welder costs about 150,000 yuan ($23,200) a year. A typical welding robot, which is sold for 120,000 yuan, can replace up to three workers a year and “doesn’t complain at work,” said the investor. A quality robot can work continuously for six to eight years, so the financial incentive to automate is obvious.

Advanced manufacturing is not just helping local bosses. It will eventually increase foreign enterprises’ dependence on China for its efficiency, making it hard to cut off Chinese supply chains despite efforts to avoid the geopolitical risks of manufacturing in China.

“In electronics, for example, most of the supply chains are in China, so factories outside China end up spending more on logistics to move parts around. Much of the 3C manufacturing is already highly automated, which relies heavily on electricity, but in most emerging economies, the power supply is still quite unstable, which disrupts production,” said Huang.

War on internet titans

The shock of antitrust regulations against Alibaba from last year is still reverberating, but another wave of scrutiny has already begun. Shortly after Didi’s blockbuster IPO in New York, the ride-hailing giant was asked to cease user registration and work on protecting user information critical to national security.

On Tuesday, Tencent stocks fell the most in a decade after it halted user signups on its WeChat messenger as it “upgrades” its security technology to align with relevant laws and regulations. The gaming and social media giant is just the latest in a growing list of companies hit by Beijing’s tightening grip on the internet sector, which had been flourishing for two decades under laissez-faire policies.

Underlying the clampdowns is Beijing’s growing unease with the service industry’s unscrutinized accumulation of wealth and power. China is unequivocally determined to advance its tech sector, but the types of tech that Beijing wants are not so much the video games that bring myopia to children and algorithms that get adults hooked to their screens. China makes it clear in its five-year plan, a series of social and economic initiatives, that it will go all-in on “hard tech” like semiconductors, renewable energy, agritech, biotech and industrial automation like factory robotics.

China has also vowed to fight inequality in education and wealth. In the authorities’ eyes, expensive, for-profit after-schools dotting big cities are hindering education attainment for children from poorer areas, which eventually exacerbates the wealth gap. The new regulatory measures have restricted the hours, content, profits and financing of private tutoring institutions, tanking stocks of the industry’s top companies. Again, there have been clear indications from President Xi Jinping’s writings to bring off-campus tutoring “back on the educational track.” All China-focused investors and analysts are now poring over Xi’s thoughts and directives.

Semiconductor wafer producer SK Siltron to invest $300M in US to boost EV supply chain

The United States has fallen behind China and Europe in the production and adoption of electric vehicles, especially from 2017 to 2020, according to a study by the International Council on Clean Transportation. One important piece of the puzzle that the U.S. does have supremacy in, however, is the production of semiconductors, which are used in everything from smartphones to computers to electric vehicles. Now, it might be strengthening that hold.

SK Siltron CSS, a unit of South Korean semiconductor wafer manufacturer SK Siltron, announced Wednesday plans to invest $300 million and create up to 150 high-paying, skilled jobs in Bay County, Michigan, which is a couple of hours north of Detroit, the country’s first automaking haven. The wafer manufacturer already has a presence in nearby Auburn, so the new factory will more than double its employee base. Over the next three years, SK Siltron says its investment will provide manufacturing and R&D capabilities of advanced materials for electric vehicles.

SK Siltron CSS chief executive Jianwei Dong told Reuters, which first reported the news, the $300 million investment would “help develop a domestic EV supply chain based in Michigan because we have our end customers in nearby communities.”

This new investment comes amid an ever-increasing lineup of new electric vehicles and investments in electrification from American automakers, including legacy companies General Motors and Ford, as well as Tesla and upstarts such as Rivian.

It’s also joining the sticky pot of trade wars between China and the U.S.

China has owned EV production globally, producing 44% of all vehicles made from 2010 to 2020, but the U.S. has put a strangle hold on semiconductors, consistently blocking China from acquiring other chipmakers. Strong policies that both invest in EV production and spur demand have proven successful in both China and Europe, according to the ICCT report. The Biden administration’s call for $174 billion in funding to expand EV subsidies and charging networks could help the country catch up.

“As we build toward a more sustainable future, it is important that we create new, robust supply chains in the U.S. to support our corporations and the end consumer,” said U.S. Secretary of Commerce Gina M. Raimondo in a statement. “The automotive industry has a tremendous opportunity with the rise of the electric vehicle, and we’re excited to see companies like SK Siltron CSS expanding to help support the transition to a green future.”

The SK Siltron CSS expansion still needs approval from state and local authorities, the company said, although it’s unlikely it will meet much resistance. The Michigan Economic Development Corporation said the state has been trying to attract EV-related jobs, spending nearly $9 billion in investments over the last two years and adding more than 10,000 jobs for the EV transition. SK Siltron said as it works with the state and local agencies to find employees, 70% will be skilled workers and the rest will be professional engineers.

Wafers 101

A wafer is a thin slice of semiconductor that’s used to make integrated circuits, which essentially help make semiconductor chips smaller and faster. The wafer serves as the base upon which the rest of the semiconductor is built, making it a crucial ingredient to the whole process. EVs need semiconductors because they allow batteries to operate at higher voltages, drive the powertrain and support modern car features like touchscreen interactivity.

SK Siltron’s wafer is made of silicon carbide, which can handle higher powers and conduct heat better than normal silicon, the company says.

“When used in EV system components, this characteristic can allow a more efficient transfer of electricity from the battery to the motor, increasing the driving range of an EV by 5% to 10%,” the company said in a statement.

The wafers can also be used in 5G communications equipment, and Dong told Reuters that the company is also considering additional investments.

GM, LG Chem studying the feasibility of a second battery cell plant in the U.S.

General Motors is exploring building a second U.S. battery cell manufacturing plant with its joint-venture partner Seoul, South Korea-based LG Chem.

If the plant moves forward, it would be the latest in a series of investments aimed at building out the auto giant’s portfolio of electric vehicles. The company’s joint venture with LG, Ultium Cells LLC, is already at work constructing a $2.3 billion battery cell manufacturing facility in Lordstown, Ohio.

The companies hope to have a decision on the factory in the first half of 2021, GM spokesman Dan Flores told TechCrunch. He declined to specify possible locations for the site but Tennessee is high on the list, according to reporting from the Wall Street Journal.

GM has set ambitious targets for decarbonizing its operations and pledged steep investments to get there. Through 2025 alone the company said it would bring thirty EV models across its brands to the global market and spend $27 billion on electrification and automated technology—a 35% increase from 2020 spending. By the mid-2030s, GM said its fleet will be all-EV.

“Clearly, with our commitment to an all-electric future, we will need a lot of battery cells,” Flores said.

He declined to comment on the ongoing shortage of battery cells, which has affected EV manufacturers Tesla and Nikola. President Joe Biden issued an executive order at the end of February instructing federal agencies to identify risks in the supply chains for batteries, semiconductors, and other critical items, including where supply chains are dependent on “competitor nations.”

GM CEO Mary Barra said in a virtual investor presentation last week that the battery shortage is one reason the company is investing in its own battery cell manufacturing. She alluded to plans to grow the company’s battery cell manufacturing operations but did not go into specifics.

“There’s more coming than we’ve announced already,” she said.

The Trump administration will add SMIC, China’s largest chipmaker, to its defense blacklist: report

SMIC, one of largest chip makers in the world, is among several companies that the Department of Defense plans to designate as being owned or controlled by the Chinese military, reports Reuters. Earlier this month, President Donald Trump signed an executive order, set to go into effect on January 11, that would bar U.S. investors from buying securities from companies on the defense blacklist.

In a statement to Reuters, SMIC said it continues “to engage constructively and openly with the U.S. government” and that it “has no relationship with the Chinese military and does not manufacture for military end-users or end-uses.”

The largest semiconductor maker in China, SMIC holds about 4% of the worldwide foundry market, estimates market research firm TrendForce. Its U.S. customers have included Qualcomm, Broadcom and Texas Instruments.

There are currently 31 companies on the defense blacklist. SMIC is one of four new companies that the Department of Defense plans to add, according to Reuters. The others are China Construction Technology, China International Engineering Consulting Corp and China National Offshore Oil Corp (CNOOC).

The company delisted from NYSE in May 2019, but it said that the decision was prompted by the limited trading volume and high administrative costs, not the U.S.-China trade war or the U.S. government’s blacklisting of Huawei and other Chinese tech companies.

SMIC has already been impacted by export restrictions that prevent them from purchasing key equipment from American suppliers. At the beginning of October, it told shareholders that export restrictions set by the U.S. Bureau of Industry and Security could have “material adverse effects” on its production.

The executive order, and the possible addition of new companies to the defense blacklist, is in-line with the Trump administration’s hard stance against Chinese tech companies, including Huawei, ZTE and ByteDance, that it claims are a potential national security threat through their alleged ties to the Chinese government and military. But the future of a lot of the current administration’s policies after the Joe Biden assumes the presidency on January 20 is uncertain.

TechCrunch has contacted SMIC for comment.

Intel agrees to sell its NAND business to SK Hynix for $9 billion

SK Hynix, one of the world’s largest chip makers, announced today it will pay $9 billion for Intel’s flash memory business. Intel said it will use proceeds from the deal to focus on artificial intelligence, 5G and edge computing.

“For Intel, this transaction will allow us to to further prioritize our investments in differentiated technology where we can play a bigger role in the success of our customers and deliver attractive returns to our stockholders,” said Intel chief executive officer Bob Swan in the announcement.

The Wall Street Journal first reported earlier this week that the two companies were nearing an agreement, which will turn SK Hynix into one of the world’s largest NAND memory makers, second only to Samsung Electronics.

The deal with SK Hynix is the latest one Intel has made so it can double down on developing technology for 5G network infrastructure. Last year, Intel sold the majority of its modem business to Apple for about $1 billion, with Swan saying that the time that the deal would allow Intel to “[put] our full effort into 5G where it most closely aligns with the needs of our global customer base.”

Once the deal is approved and closes, Seoul-based SK Hynix will take over Intel’s NAND SSD and NAND component and wafer businesses, and its NAND foundry in Dalian, China. Intel will hold onto its Optane business, which makes SSD memory modules. The companies said regulatory approval is expected by late 2021, and a final closing of all assets, including Intel’s NAND-related intellectual property, will take place in March 2025.

Until the final closing takes places, Intel will continue to manufacture NAND wafers at the Dalian foundry and retain all IP related to the manufacturing and design of its NAND flash wafers.

As the Wall Street Journal noted, the Dalian facility is Intel’s only major foundry in China, which means selling it to SK Hynix will dramatically reduce its presence there as the United States government puts trade restrictions on Chinese technology.

In the announcement, Intel said it plans to use proceeds from the sale to “advance its long-term growth priorities, including artificial intelligence, 5G networking and the intelligent, autonomous edge.”

During the six-month period ending on June 27, 2020, NAND business represented about $2.8 billion of revenue for its Non-volatile Memory Solutions Group (NSG), and contributed about $600 million to the division’s operating income. According to the Wall Street Journal, this made up the majority of Intel’s total memory sales during that period, which was about $3 billion.

SK Hynix CEO Seok-Hee Lee said the deal will allow the South Korean company to “optimize our business structure, expanding our innovative portfolio in the NAND flash market segment, which will be comparable with what we achieved in DRAM.”

Microsoft, Amazon back a SoCal company making microchips specifically for voice-based apps

Microsoft’s venture capital fund, M12 Ventures, has led a slew of strategic corporate investors backing a new chip developer out of Southern California called Syntiant, which makes semiconductors for voice recognition and speech-based applications.

“We started out to build a new type of processor for machine learning, and voice is our first application,” says Syntiant chief executive Kurt Busch. “We decided to build a chip for always-on battery-powered devices.”

Those chips need a different kind of processor than traditional chipsets, says Busch. Traditional compute is about logic, and deep learning is about memory access; traditional microchip designs also don’t perform as well when it comes to parallel processing of information.

Syntiant claims that its chips are two orders of magnitude more efficient, thanks to its data flow architecture that was built for deep learning, according to Busch.

It’s that efficiency that attracted investors, including M12, Microsoft Corp.’s venture fund; the Amazon Alexa Fund; Applied Ventures, the investment arm of Applied Materials; Intel Capital; Motorola Solutions Venture Capital; and Robert Bosch Venture Capital.

These investment firms represent some of the technology industry’s top chip makers and software developers, and they’re pooling their resources to support Syntiant’s Irvine, California-based operations.

smart speakers

Image Credits: Bryce Durbin / TechCrunch

“Syntiant aligns perfectly with our mission to support companies that fuel voice technology innovation,” said Paul Bernard, director of the Alexa Fund at Amazon. “Its technology has enormous potential to drive continued adoption of voice services like Alexa, especially in mobile scenarios that require devices to balance low power with continuous, high-accuracy voice recognition. We look forward to working with Syntiant to extend its speech technology to new devices and environments.” 

Syntiant’s first device measures 1.4 by 1.8 millimeters and draws 140 microwatts of power. In some applications, Syntiant’s chips can run for a year on a single coin cell.

“Syntiant’s neural network technology and its memory-centric architecture fits well with Applied Materials’ core expertise in materials engineering as we enable radical leaps in device performance and novel materials-enabled memory technologies,” said Michael Stewart, principal at Applied Ventures, the venture capital arm of Applied Materials, Inc. “Syntiant’s ultra-low-power neural decision processors have the potential to create growth in the chip marketplace and provide an effective solution for today’s demanding voice and video applications.” 

So far, 80 customers are working with Syntiant to integrate the company’s chips into their products. There are a few dozen companies in the design stage and the company has already notched design wins for products ranging from cell phones and smart speakers to remote controls, hearing aids, laptops and monitors. Already the company has shipped its first million units.  

“We expect to scale that by 10x by the end of this year,” says Busch. 

Syntiant’s chipsets are designed specifically to handle wakes and commands, which means that users can add voice recognition features and commands unique to their particular voice, Busch says.

Initially backed by venture firms including Atlantic Bridge, Miramar and Alpha Edison, Syntiant raised its first round of funding in October 2017. The company has raised a total of $65 million to date, according to Busch.

“Syntiant’s architecture is well-suited for the computational patterns and inherent parallelism of deep neural networks,” said Samir Kumar, an investor with M12 and new director on the Syntiant board. “We see great potential in its ability to enable breakthroughs in power performance for AI processing in IoT [Internet of things].”