Month: April 2018

Reports of an active shooter at YouTube’s San Bruno, CA headquarters have been reported on social media.

We will update this story as we learn more. 

Source: Tech Crunch

Spotify is done with its long-awaited “direct listing” experiment. The music streaming company went public without the IPO.

After completing its first trade halfway through the day at $165.90, Spotify fell to $149.60. It was a down day on the stock market, but at a $26.6 billion market cap, it’s up from the private market trading that happened in the months leading up to the IPO.

The top end of that range, $132, was used as a “reference point,” valuing the company at $23.5 billion. Since there was no IPO price, that demarcation is being used to say that Spotify traded up about 13% on its first day.

Yet while it achieved a desirable market cap, some on Wall Street are puzzled as to why Spotify would want to go public without raising money.

One myth that’s been floating around is that Spotify did this to avoid paying bankers. In fact, they worked with Morgan Stanley, Goldman Sachs and Allen & Co. in the lead up to the debut.

They did not eliminate the investment banks, but they did manage to avoid the dreaded “lock-up” expiration, which is when most employees and insiders are allowed to sell shares. This is usually about six months after an IPO.

Some are wondering if Spotify’s debut will be replicated in the future.

“The direct listing is really interesting as a potential roadmap for future companies because the price that Spotify now trades it as a real price without any of the distortions which come from a lockup or a banker-managed process,” said Chi-Hua Chen, managing partner at Goodwater Capital. Chen invested in Spotify when he was at Kleiner Perkins. He believes that “the price is as real an expression of the value of the company as possible, which makes it an interesting case study for future companies moving into the public markets.”

Apart from the change in process, this debut also felt different from IPOs because there was no celebration. There was no bell-ringing and no Spotify employees cheering from the floor.

Outside the New York Stock Exchange, there was a Spotify banner to commemorate the event. And next to it, there was a Swiss flag meant to honor them. The only problem is, Spotify is Swedish.

Source: Tech Crunch

If you’re running a software company today, it’s almost a foregone conclusion that most or all of your apps will run in the cloud. Likely Amazon or Google’s. It’s hard to imagine that this wasn’t always the case, but there are still some late adopters migrating their own physical data centers into managed ones. And, as with all trends in technology, this too shall pass. Just when you were getting comfortable with containers and auto-scaling, a new architecture emerges, swinging the pendulum back to a truly distributed world.

What’s wrong with the cloud?

A typical self-driving car generates up to 100MB of data per second from a combination of cameras, LIDARs, accelerometers and on-board computers. That data needs to be processed nearly instantly to keep the car on the road. With so much data to sift through, the current generation of cellular networks can’t keep up. By the time data arrives in the cloud, it will be too late. Instead, data needs to be processed as close to the sensors as possible, directly at the edge of networks, on the cars themselves.

Most of us aren’t building or riding in self-driving cars (yet), but there’s a good chance we’re already interacting with edge computing every day. Neural networks in smart speakers in almost 40 million American homes are listening for words like “Alex,” “Siri” or “Google” and, according to Statista, 3 billion Snapchats are scanned for faces each day in order to add the addicting face filters. By the end of the year, 20 percent of smartphones globally will have hardware-accelerated machine learning capabilities.

How did we get here?

All of these apps and devices are made possible by two major trends: advances in deep learning algorithms that help computers see, hear and understand and the proliferation of specialized processors like GPUs and TPUs that can run these algorithms efficiently, even in mobile environments.

Neural networks and deep learning aren’t new. In fact, the first artificial neural networks were created in the 1950s, and there have been multiple false starts since.This time, though, the abundance of labeled training data and compute power made it feasible to train these large models. Though AI research is still proceeding at a breakneck pace, fields like computer vision are starting to mature. Developers can choose from a variety of standardized model architectures, publicly available training data sets and tools. You no longer need a PhD just to get started. Technology is being democratized.

Hardware is catching up, fast. Machine learning algorithms like neural networks are really just long sequences of matrix multiplications. Specialized processors like GPUs and newer neural processing units like those in Apple’s A11 Bionic chip and Google’s Tensor Processing Unit (TPU) are optimized for exactly these mathematical operations, offering 10-100x speedups over traditional CPUs while using less power overall. As major chip manufacturers roll out mobile-ready machine learning accelerators, every device will soon have the power to run the latest AI models.

The edge = new opportunity

Big data, data science, machine learning and now deep learning have been slowly weaving their way into products and companies for the past decade. Most of the time, this happened behind the scenes, up in the cloud. Data warehouses and analytics pipelines process records en masse. Results are made accessible to end users through APIs and database queries. That’s not going away, but the edge presents a new opportunity to use the predictive capabilities of machine learning models more quickly.

Now, the algorithms move to the data. Information is processed in real time, as soon as it’s captured by the sensor, and results are available immediately. In this latency-free world, entirely new user experiences are possible. Your phone’s screen becomes a portal to a world of augmented reality. Products can be personalized for a single user while private data never leaves the device. Applications become ambient and frictionless, anticipating questions and answering them before you ask.

It doesn’t take a PhD

When done right, experiences made with AI and edge computing feel like magic, but building them is incredibly complex. There is a divide between the tech stacks used to train and deploy machine learning models in the cloud and the ones used to build applications for edge devices, like smartphones and IoT. Neural networks can replace thousands of lines of procedural code, but fail in unexpected, silent ways and need to be tested differently. Performance issues that can be solved by simply adding more compute or memory from a near infinite cloud call for specialized optimization when they occur out on edge devices we don’t control. Even the programming languages preferred by the cloud are different than those running applications on mobile devices.

This is starting to change. Tools and hardware are improving so quickly it’s hard to keep up. Heavyweights like Apple and Google have made mobile machine learning frameworks (Core ML and TensorFlow Lite, respectively) centerpieces of their latest developer offerings. More export options and better interoperability are being added to tools like AWS’s SageMaker, Azure’s ML Studio and IBM’s Watson Studio weekly.

Source: Tech Crunch

For those who live under a rock (which, these days, I would recommend), President Donald Trump has become increasingly belligerent towards Amazon and its founder, Jeff Bezos.

In addition to a sequence of tweets against the ecommerce and cloud giant , Gabriel Sherman reported in Vanity Fair yesterday that “Now, according to four sources close to the White House, Trump is discussing ways to escalate his Twitter attacks on Amazon to further damage the company. ‘He’s off the hook on this. It’s war,’ one source told me. ‘He gets obsessed with something, and now he’s obsessed with Bezos,’ said another source. ‘Trump is like, how can I fuck with him?’”

‘How can I fuck with them?’ could also describe America’s backwards approach to its flagging prowess in critical technology fields, policies that stand in stark contrast to the massive and focused investment of strategic adversaries like China.

Through its Made in China 2025 plan, China is putting in place a series of initiatives to dominate the future of technologies like 5G wireless networking, artificial intelligence, cloud computing, biotechnology, and semiconductors. It is working to raise about $36 billion for a new semiconductor fund, potentially spend $411 billion on 5G infrastructure, and create a massive domestic market for overseas stocks through Chinese Depositary Receipts.

China selects, grows, and champions a set of winners in each industry in order to concentrate resources and increase the probability of success globally for its chosen companies. As Antonio Graceffo described in Foreign Policy Journal, “National champions are companies which help further the government’s strategic aims and in return, the government supports these companies by providing easier access to financing, giving preference in government contract bidding, and sometimes oligarchy or monopoly status in protected industries, giving these companies a number of advantages over their competitors.”

One has to look no further than Huawei to see the benefits of these policies. Huawei was an unknown player when it started roughly three decades ago, but through an aggressive expansion plan and a wellspring of government support, it has emerged to be the single largest manufacturer of telecommunications networking equipment in the world, surpassing Ericsson back in 2012. The company had revenues of $92 billion last year, and it is taking an early lead in the 5G wireless standards race, which could give it a powerful position to shape the future of connectivity in the years to come.

Meanwhile, the leadership of the United States is increasingly targeting the tech sector — one of the few areas of true vibrancy in the American economy — and trying to undermine it at every turn. The Trump administration has announced tariffs on high-tech goods that will end up harming U.S. technology exports, rolled back net neutrality legislation, and now is talking out loud about breaking up Amazon through antitrust laws.

On the latter, it’s not just Trump calling for war against America’s tech leaders: there is a growing movement against companies like Google and Apple which has led to increasing calls for antitrust action from both right-wing and left-wing policy analysts.

There are good reasons to be concerned about market dominance — it limits consumer choice and often rises prices. However, there are obvious limitations on how many competitors can enter markets like wireless infrastructure and cloud computing. The upfront costs are exorbitant — just launching a single data center today can easily cost hundreds of millions of dollars or more, and conducting original R&D in a competitive industry like artificial intelligence is equally expensive when a machine learning expert can go for tens of millions of dollars.

We are never going to have five Googles, nor five Dropboxes or five Amazons — the economics in these markets just don’t work that way. Their scale is what allows them to offer such comprehensive services at such low cost to consumers. Knocking out Apple is really opening the American market to the next four smartphone manufacturers, which would be Asian manufacturers like Samsung, Huawei, Lenovo, and Xiaomi. That sounds like a pyrrhic victory to me.

The U.S. believes in the power of free markets to cull losers and ensure winners a fair return, and the government avoids picking “winners” as a matter of course in its industrial policy. That worked great when the American economy was dominant, but it is no longer tenable in a world where strategic adversaries are putting their full weight behind a handful of companies.

So instead of getting on The Twitter and blasting Amazon, maybe this administration should start to consider that Amazon’s size and dominance in ecommerce and cloud services is actually an incredible blessing of American capitalism. Maybe it should start to think about how the govenrmetn could assist Amazon in capturing more overseas markets, ensuring that the wealth generated by the company continues to return to its home country.

The threats faced by American tech companies parallel similar fears of the 1980s, when Japan’s resurgence on the world stage captivated the attention of U.S. politicians. China though is nearly eleven times the population of Japan, and has already overtaken the U.S. economy by some measures. This time really is very different, and the free market needs defenders. Ironically, that means backing American tech giants globally against their competitors.

Source: Tech Crunch

MIT is disassociating itself from Nectome, the Y Combinator-backed startup promising to preserve customers’ brains for the possibility of future digital upload.

Co-founder Robert McIntyre described the procedure as “100 percent fatal” — it involves connecting terminally ill patients to a machine that pumps embalming fluids into their arteries.

The company has collected (refundable) $10,000 payments for a wait list, but its website now carries a note in “response to recent press,” suggesting that the company would only carry the procedure out after further research:

We believe that clinical human brain preservation has immense potential to benefit humanity, but only if it is developed in the light, with input from medical and neuroscience experts. We believe that rushing to apply vitrification today would be extremely irresponsible and hurt eventual adoption of a validated protocol.

As noted in the MIT Technology Review, MIT has been criticized for potentially giving the company credibility by association — MIT Media Lab professor Edward Boyden was receiving money through a federal grant won by Nectome. (McIntyre and his co-founder Michael McCanna are both MIT graduates.)

Now the Media Lab has released a statement saying that after reviewing “the scientific premises underlying the company’s commercial plans, as well as certain public statements that the company has made,” it will “terminate the subcontract between MIT and Nectome in accordance with the terms of their agreement.”

The Media Lab says that the grant involved a research project to “combine aspects of Nectome’s chemistry with the Boyden group’s invention, expansion microscopy, to better visualize mouse brain circuits for basic science and research purposes.” Apparently Prof. Boyden has “no personal affiliation — financial, operational, or contractual — with the company Nectome.”

The statement concludes with a discussion of the science behind Nectome. The Media Lab doesn’t completely rule out the possibility of brain preservation and uploading in the future, but it suggests that science isn’t solid yet:

Neuroscience has not sufficiently advanced to the point where we know whether any brain preservation method is powerful enough to preserve all the different kinds of biomolecules related to memory and the mind. It is also not known whether it is possible to recreate a person’s consciousness.

McIntyre told the Technology Review, “We appreciate the help MIT has given us, understand their choice, and wish them the best.”

Source: Tech Crunch

Fitbit shaved off another roughly 10% of its value in trading today after a downgrade from a Wall Street firm, which will once again throw on more skepticism as to whether or not Fitbit can be a viable business in the smartwatch market.

The note came from Morgan Stanley this morning, which said it was “hard to see a floor” for the company. This comes amid an increased push from Apple to position its smartwatch as a health-oriented device through a myriad of updates for its health tools, as well as efforts to actually detach it from your smartphone with its own cellular chip. These kinds of notes often tend to send stocks soaring or tumbling depending on the direction they go in as investors look to better calibrate their positions in the market.

Fitbit is working on its next generation of smartwatches that look to go up against the Apple Watch, including the new Fitbit Versa, which my colleague Brian Heater said was the watch “the smartwatch the Ionic should have been” (Fitbit’s first foray into the smartwatch ecosystem, which was a bust). The company is also working on a fitness tracker for kids, and appears to be still doubling down on that health aspect of its wearables that first made it a popular choice among consumers in the first place. Fitbit also bought Twine, a cloud-based health management platform, in February.

Here’s another one of the rough excerpts from the note published by CNBC: “We think new smartwatches will be outweighed by declines in legacy products, while software opportunities in health coaching will take time to ramp.”

Fitbit made its name as a fitness tracker, but Apple increasingly has come out pitching itself not only as a fitness tracker, but one with a robust toolkit for health in general. In addition to a heart monitor, Apple has the ability to create a whole health software ecosystem tied directly into the iPhone, which apps like MyFitnessPal and others can use for data. So Apple will clearly be the biggest hurdle for Fitbit as it looks to figure out what its next-generation fitness wearable looks like, especially as Apple if Apple looks to continue to drop the price of the Apple Watch.

Source: Tech Crunch

Who would have thought a potential trade war would cause investors to sell?

U.S. markets plunged today as China announced that it was implementing tariffs on $3 billion worth of American goods, mostly in agriculture and steel production. The Dow was down nearly 600 points today an hour before markets closed, and the NASDAQ was down about 210 points, or roughly 2.92%.

Investors are skittish that a festering trade skirmish will grow into a full on trade war. Even though these Chinese tariffs weren’t directed at high-tech goods, investors expect that any trade fight will ultimately hit the sector the hardest, since American exports to China are predominantly in areas like aircraft, machinery, and electronics. Tech stocks were almost universally down today except for a handful of smaller players.

China’s proposed tariffs are 15% on 120 categories of goods including dried apples, frozen strawberries, unshelled chestnuts, sparkling wine, and various types of stainless steel piping and casings. The Chinese are going to levy a higher 25% tariff on pork products and aluminum scrap coming from the United States. The tariffs were implemented today, and are retaliation to the Trump administration’s announcement that it would place tariffs on steel and aluminum imports. China has not yet responded with a retaliatory tariff for Trump’s tariff on $60 billion of electronic goods, which have not yet been brought into force.

Increasing tariffs is an unusual event in a world that has made free trade agreements a major force for diplomacy over the past three decades. China joined the World Trade Organization in 2001, but market liberalization has lagged, and there are increasing constituencies in the United States and in other Western nations to reverse these trade agreements and cut a new deal.

Much as the United States is preparing a fusillade of techniques to slow down Chinese trade, the Chinese government is also attempting to use various powers to fight back. Qualcomm is still waiting for approval from China’s government for its acquisition of NXP Semiconductors, a massive deal at the heart of one of America’s most prominent technology leaders. China is also considering creating Chinese Depositary Receipts to mobilize local dollars and “buy back” local tech behemoths like Alibaba and Tencent, potentially creating a new trillion dollar local asset market.

On the American side, U.S. Trade Representative Robert Lighthizer was quoted last week saying that a computer algorithm would try to select goods that maximize the harm to China’s trade, while minimizing the damage to American consumers. That’s gradient descent into trade oblivion.

It’s a multidimensional game, with both sides using tactics that would have been completely dismissed by policymakers just a year or two ago. Expect more gyrations in the markets in the coming weeks as we learn more about Trump’s proposed electronics tariffs, and the Chinese response to them.

Source: Tech Crunch

Apple is planning to use its own chips for its Mac devices, which could replace the Intel chips currently running on its desktop and laptop hardware, according to a report from Bloomberg.

Apple already designs a lot of custom silicon, including its chipsets like the W-series for its Bluetooth headphones, the S-series in its watches, its A-series iPhone chips, as well as customized GPU for the new iPhones. In that sense, Apple has in a lot of ways built its own internal fabless chip firm, which makes sense as it looks for its devices to tackle more and more specific use cases and remove some of its reliance on third parties for their equipment. Apple is already in the middle of in a very public spat with Qualcomm over royalties, and while the Mac is sort of a tertiary product in its lineup, it still contributes a significant portion of revenue to the company.

Creating an entire suite of custom silicon could do a lot of things for Apple, the least of which bringing in the Mac into a system where the devices can talk to each other more efficiently. Apple already has a lot of tools to shift user activities between all its devices, but making that more seamless means it’s easier to lock users into the Apple ecosystem. If you’ve ever compared connecting headphones with a W1 chip to the iPhone and just typical Bluetooth headphones, you’ve probably seen the difference, and that could be even more robust with its own chipset. Bloomberg reports that Apple may implement the chips as soon as 2020.

Intel may be the clear loser here, and the market is reflecting that. Intel’s stock is down nearly 8% after the report came out, as it would be a clear shift away from the company’s typical architecture where it has long held its ground as Apple moves on from traditional silicon to its own custom designs. Apple, too, is not the only company looking to design its own silicon, with Amazon looking into building its own AI chips for Alexa in another move to create a lock-in for the Amazon ecosystem. And while the biggest players are looking at their own architecture, there’s an entire suite of startups getting a lot of funding building custom silicon geared toward AI.

Apple declined to comment.

Source: Tech Crunch