Google today announced that it will invest $13 billion in data centers and offices across the U.S. in 2019. That’s up from $9 billion in investments last year. Many of these investments will go to states like Nebraska, Nevada, Ohio, Texas, Oklahoma, South Carolina and Virginia, where Google plans new or expanded data centers. Though like most years, it’ll also continue to expand many of its existing offices in Seattle, Chicago and New York, as well as in its home state of California.
Given Google’s push for more cloud customers, it’s also interesting to see that the company continues to expand its data center presence across the country. Google will soon open its first data centers in Nevada, Nebraska, Ohio and Texas, for example, and it will expand its Oklahoma, South Carolina and Virginia data centers. Google clearly isn’t slowing down in its race to compete with AWS and Azure.
“These new investments will give us the capacity to hire tens of thousands of employees, and enable the creation of more than 10,000 new construction jobs in Nebraska, Nevada, Ohio, Texas, Oklahoma, South Carolina and Virginia,” Google CEO Sundar Pichai writes today. “With this new investment, Google will now have a home in 24 total states, including data centers in 13 communities. 2019 marks the second year in a row we’ll be growing faster outside of the Bay Area than in it.”
Given the current backlash against many tech companies and automation in general, it’s probably no surprise that Google wants to emphasize the number of jobs it is creating (and especially jobs in Middle America). The construction jobs are obviously temporary, though, and data centers don’t need a lot of employees to run once they are up and running. Still, Google promises that this will give it the “capacity to hire tens of thousands of employees.”
The shine on Apple is getting a little tarnished. Today, the SEC filed a suit against Gene Levoff, a lawyer who used to work for the iPhone giant, accusing him of insider trading, selling millions of dollars in stock ahead of earnings and saving himself some $382,000 in losses the process, and in a separate, earlier period, $245,000 in profits.
Levoff started to work for Apple in 2008, first as director of corporate law and then senior director. He was put on leave from Apple in July 2018, and his employment was terminated in September 2018.
The suit covers activities 2015 and 2016, years when Apple saw a dip in performance before it roared back with a trillion dollar market cap in 2017.
The news is especially ironic — although perhaps not surprising, considering the information Levoff had at his disposal: he had been the company’s Senior Director of Corporate Law and Corporate Secretary of Apple and was “responsible for ensuring compliance with the company’s insider trading policy and determining the criteria for those employees (including himself) restricted from trading around quarterly earnings announcements.”
It also worked in the other direction. The SEC alleges that Levoff also made trades in 2011 and 2012 also ahead of market-moving news that helped him make profits of $245,000.
The SEC is requesting that Levoff pay a civil monetary penalty, disgorging “an amount equal to the profits gained and losses avoided as a result of the actions described herein,” and that he be prohibited from serving as an officer or director of a public company.
The SEC suit covers trades on “at least” three occasions between 2015 and 2016, where Levoff would have access to financial data before it was released to the public and subsequently make trades on that information.
One example noted in the suit notes that he sold $10 million in stock in July ahead of Apple reporting that it would miss expectations on iPhone sales.
The SEC makes a point of noting the disconnect between Levoff’s actions for his own gain and his role at the company. Among his duties was serving on Apple’s Disclosure Committee,
“established to assist the Chief Executive Officer and Chief Financial Officer in fulfilling their responsibility for oversight of the accuracy and timeliness of disclosures made by Apple; determine Apple’s disclosure obligations and ensure information contained in Apple’s filings to the SEC and all other disclosures are timely, accurate, complete, and a fair representation of Apple’s financial condition and results of operations; and ensure that Apple’s disclosure controls and procedures are properly designed, adopted and implemented.”
Levoff was involved with some of the stealthier parts of Apple’s dealings. His name also appears involved with a number of Apple’s M&A deals, with his name coming up as a director on legal documents of startups that Apple had quietly acquired in Europe. He was also named in an investigation into how Apple funnels profits into offshore accounts.
But in this suit, the SEC makes a point of clearing Apple itself of wrongdoing in the specific case of insider trading, noting that the company took several steps to warn employees of blackout periods and general legal and illegal practices regarding trading and financial information (some of which Levoff himself even penned):
“Prior to Levoff’s illegal trading, Apple took steps to prevent employees from trading on material nonpublic information, including the undisclosed financial results Levoff received,” it notes. “Apple had an insider trading policy that applied to all employees. Many employees, including Levoff, also received notice when restricted trading periods, known as “blackout” periods, were in effect. The notices, emailed to employees subject to the blackout periods, reminded them of the insider trading policy, and since at least 2015, included a link to the insider trading policy.”
The news is pretty explosive, in the context both of Apple being one of the more tight-lipped companies and generally positioning itself as a model corporate citizen, taking a strong stand not just on issues like user privacy but priding itself on strong customer products and service, at a premium price compared to much of the competition.
We have reached out to Apple for comment, and will update this post as we learn more.
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Moving the Manage Subscriptions menu so that it’s just one click away from your App Store profile might seem like a minor change, but it was needed: As more mobile apps have adopted subscriptions as a means of generating revenue, it’s become critical to ensure consumers know how to turn off their subscriptions.
Plus, Apple is expected to launch some subscriptions of its own, namely for its streaming video and news services.
Don’t panic! Instagram says it’s “aware of an issue that is causing a change in account follower numbers for some people right now” and is “working to resolve this as quickly as possible.”
The latest figures out of NPD show a continued uptick in smartwatch sales here in the States. The category has been a rare bright spot in an overall flagging wearable space, and the new numbers show gains pretty much across the board.
Founded in 1999 by brothers Evan and Gregg Spiridellis after they saw “an animated dancing doodie streaming over a 56K modem,” JibJab’s big break came during the 2004 presidential campaign, when its satirical “This Land” racked up more than 80 million views.
Eight has been focused on bed temperature for a while, first by offering a smart mattress cover and then a smart mattress that allows owners to adjust the surface temperature and even set different temperatures for different sides of the bed. But The Pod goes even further, with a smart temperature mode that will change bed temperature throughout the night to improve your sleep.
Clever-Commit is an assistant that learns from your code base’s bug and regression data to analyze and flag potential new bugs as new code is committed.
“If AI is so easy, why isn’t there any in this room?” asks Ali Farhadi, founder and CEO of Xnor, gesturing around the conference room overlooking Lake Union in Seattle. And it’s true — despite a handful of displays, phones, and other gadgets, the only things really capable of doing any kind of AI-type work are the phones each of us have set on the table. Yet we are always hearing about how AI is so accessible now, so flexible, so ubiquitous.
And in many cases even those devices that can aren’t employing machine learning techniques themselves, but rather sending data off to the cloud where it can be done more efficiently. Because the processes that make up “AI” are often resource-intensive, sucking up CPU time and battery power.
The team achieved that, and Xnor’s hyper-efficient ML models are now integrated into a variety of devices and businesses. As a follow-up, the team set their sights higher — or lower, depending on your perspective.
Answering his own question on the dearth of AI-enabled devices, Farhadi pointed to the battery pack in the demo gadget they made to show off the Pi Zero platform, Farhadi explained: “This thing right here. Power.”
Power was the bottleneck they overcame to get AI onto CPU- and power-limited devices like phones and the Pi Zero. So the team came up with a crazy goal: Why not make an AI platform that doesn’t need a battery at all? Less than a year later, they’d done it.
That thing right there performs a serious computer vision task in real time: It can detect in a fraction of a second whether and where a person, or car, or bird, or whatever, is in its field of view, and relay that information wirelessly. And it does this using the kind of power usually associated with solar-powered calculators.
The device Farhadi and hardware engineering head Saman Naderiparizi showed me is very simple — and necessarily so. A tiny camera with a 320×240 resolution, an FPGA loaded with the object recognition model, a bit of memory to handle the image and camera software, and a small solar cell. A very simple wireless setup lets it send and receive data at a very modest rate.
“This thing has no power. It’s a two dollar computer with an uber-crappy camera, and it can run state of the art object recognition,” enthused Farhadi, clearly more than pleased with what the Xnor team has created.
For reference, this video from the company’s debut shows the kind of work it’s doing inside:
As long as the cell is in any kind of significant light, it will power the image processor and object recognition algorithm. It needs about a hundred millivolts coming in to work, though at lower levels it could just snap images less often.
It can run on that current alone, but of course it’s impractical to not have some kind of energy storage; to that end this demo device has a supercapacitor that stores enough energy to keep it going all night, or just when its light source is obscured.
As a demonstration of its efficiency, let’s say you did decide to equip it with, say, a watch battery. Naderiparizi said it could probably run on that at one frame per second for more than 30 years.
Not a product
Of course the breakthrough isn’t really that there’s now a solar-powered smart camera. That could be useful, sure, but it’s not really what’s worth crowing about here. It’s the fact that a sophisticated deep learning model can run on a computer that costs pennies and uses less power than your phone does when it’s asleep.
“This isn’t a product,” Farhadi said of the tiny hardware platform. “It’s an enabler.”
The energy necessary for performing inference processes such as facial recognition, natural language processing, and so on put hard limits on what can be done with them. A smart light bulb that turns on when you ask it to isn’t really a smart light bulb. It’s a board in a light bulb enclosure that relays your voice to a hub and probably a datacenter somewhere, which analyzes what you say and returns a result, turning the light on.
That’s not only convoluted, but it introduces latency and a whole spectrum of places where the process could break or be attacked. And meanwhile it requires a constant source of power or a battery!
On the other hand, imagine a camera you stick into a house plant’s pot, or stick to a wall, or set on top of the bookcase, or anything. This camera requires no more power than some light shining on it; it can recognize voice commands and analyze imagery without touching the cloud at all; it can’t really be hacked because it barely has an input at all; and its components cost maybe $10.
Only one of these things can be truly ubiquitous. Only the latter can scale to billions of devices without requiring immense investment in infrastructure.
And honestly, the latter sounds like a better bet for a ton of applications where there’s a question of privacy or latency. Would you rather have a baby monitor that streams its images to a cloud server where it’s monitored for movement? Or a baby monitor that absent an internet connection can still tell you if the kid is up and about? If they both work pretty well, the latter seems like the obvious choice. And that’s the case for numerous consumer applications.
Amazingly, the power cost of the platform isn’t anywhere near bottoming out. The FPGA used to do the computing on this demo unit isn’t particularly efficient for the processing power it provides. If they had a custom chip baked, they could get another order of magnitude or two out of it, lowering the work cost for inference to the level of microjoules. The size is more limited by the optics of the camera and the size of the antenna, which must have certain dimensions to transmit and receive radio signals.
And again, this isn’t about selling a million of these particular little widgets. As Xnor has done already with its clients, the platform and software that runs on it can be customized for individual projects or hardware. One even wanted a model to run on MIPS — so now it does.
By drastically lowering the power and space required to run a self-contained inference engine, entirely new product categories can be created. Will they be creepy? Probably. But at least they won’t have to phone home.
“If AI is so easy, why isn’t there any in this room?” asks Ali Farhadi, founder and CEO of Xnor, gesturing around the conference room overlooking Lake Union in Seattle. And it’s true — despite a handful of displays, phones, and other gadgets, the only things really capable of doing any kind of AI-type work are the phones each of us have set on the table. Yet we are always hearing about how AI is so accessible now, so flexible, so ubiquitous.
And in many cases even those devices that can aren’t employing machine learning techniques themselves, but rather sending data off to the cloud where it can be done more efficiently. Because the processes that make up “AI” are often resource-intensive, sucking up CPU time and battery power.
The team achieved that, and Xnor’s hyper-efficient ML models are now integrated into a variety of devices and businesses. As a follow-up, the team set their sights higher — or lower, depending on your perspective.
Answering his own question on the dearth of AI-enabled devices, Farhadi pointed to the battery pack in the demo gadget they made to show off the Pi Zero platform, Farhadi explained: “This thing right here. Power.”
Power was the bottleneck they overcame to get AI onto CPU- and power-limited devices like phones and the Pi Zero. So the team came up with a crazy goal: Why not make an AI platform that doesn’t need a battery at all? Less than a year later, they’d done it.
That thing right there performs a serious computer vision task in real time: It can detect in a fraction of a second whether and where a person, or car, or bird, or whatever, is in its field of view, and relay that information wirelessly. And it does this using the kind of power usually associated with solar-powered calculators.
The device Farhadi and hardware engineering head Saman Naderiparizi showed me is very simple — and necessarily so. A tiny camera with a 320×240 resolution, an FPGA loaded with the object recognition model, a bit of memory to handle the image and camera software, and a small solar cell. A very simple wireless setup lets it send and receive data at a very modest rate.
“This thing has no power. It’s a two dollar computer with an uber-crappy camera, and it can run state of the art object recognition,” enthused Farhadi, clearly more than pleased with what the Xnor team has created.
For reference, this video from the company’s debut shows the kind of work it’s doing inside:
As long as the cell is in any kind of significant light, it will power the image processor and object recognition algorithm. It needs about a hundred millivolts coming in to work, though at lower levels it could just snap images less often.
It can run on that current alone, but of course it’s impractical to not have some kind of energy storage; to that end this demo device has a supercapacitor that stores enough energy to keep it going all night, or just when its light source is obscured.
As a demonstration of its efficiency, let’s say you did decide to equip it with, say, a watch battery. Naderiparizi said it could probably run on that at one frame per second for more than 30 years.
Not a product
Of course the breakthrough isn’t really that there’s now a solar-powered smart camera. That could be useful, sure, but it’s not really what’s worth crowing about here. It’s the fact that a sophisticated deep learning model can run on a computer that costs pennies and uses less power than your phone does when it’s asleep.
“This isn’t a product,” Farhadi said of the tiny hardware platform. “It’s an enabler.”
The energy necessary for performing inference processes such as facial recognition, natural language processing, and so on put hard limits on what can be done with them. A smart light bulb that turns on when you ask it to isn’t really a smart light bulb. It’s a board in a light bulb enclosure that relays your voice to a hub and probably a datacenter somewhere, which analyzes what you say and returns a result, turning the light on.
That’s not only convoluted, but it introduces latency and a whole spectrum of places where the process could break or be attacked. And meanwhile it requires a constant source of power or a battery!
On the other hand, imagine a camera you stick into a house plant’s pot, or stick to a wall, or set on top of the bookcase, or anything. This camera requires no more power than some light shining on it; it can recognize voice commands and analyze imagery without touching the cloud at all; it can’t really be hacked because it barely has an input at all; and its components cost maybe $10.
Only one of these things can be truly ubiquitous. Only the latter can scale to billions of devices without requiring immense investment in infrastructure.
And honestly, the latter sounds like a better bet for a ton of applications where there’s a question of privacy or latency. Would you rather have a baby monitor that streams its images to a cloud server where it’s monitored for movement? Or a baby monitor that absent an internet connection can still tell you if the kid is up and about? If they both work pretty well, the latter seems like the obvious choice. And that’s the case for numerous consumer applications.
Amazingly, the power cost of the platform isn’t anywhere near bottoming out. The FPGA used to do the computing on this demo unit isn’t particularly efficient for the processing power it provides. If they had a custom chip baked, they could get another order of magnitude or two out of it, lowering the work cost for inference to the level of microjoules. The size is more limited by the optics of the camera and the size of the antenna, which must have certain dimensions to transmit and receive radio signals.
And again, this isn’t about selling a million of these particular little widgets. As Xnor has done already with its clients, the platform and software that runs on it can be customized for individual projects or hardware. One even wanted a model to run on MIPS — so now it does.
By drastically lowering the power and space required to run a self-contained inference engine, entirely new product categories can be created. Will they be creepy? Probably. But at least they won’t have to phone home.
As autonomous driving eventually transforms cars from transportation devices to mobile theaters or conference rooms we will need better audio inside them. And we’ve already seen that VCs like Andreessen Horowitz say ‘audio is the future.’
So it’s interesting that Swedish sound pioneer Dirac has completed a new $13.2 million round of financing led by current investors. Previous investors included Swedish Angel network Club Network Investments, Erik Ejerhed and Staffan Persson.
Dirac makes sophisticated audio technology for customers including BMW, OnePlus, Rolls Royce, Volvo, and Xiaomi .
Its platform is used by those firms for everything from capture to playback – regardless of device size or form factor.
“As consumer devices decrease in size and expand in complexity, digital signal processing is
the key to unlocking their full audio potential and creating premium sound experiences,” says
Dirac CEO Mathias Johansson. “With this new funding, we can take our approach to digitizing
sound systems even further – creating more intelligent and adaptive audio processing solutions that establish new standards in both audio playback and capture across a variety of
applications.”
Dirac has now appointed former Harman International executive Armin Prommersberger as CTO and opened a Copenhagen Research Development Center.
Johansson says new 5G networks are set to create new use-cases for current and emerging technologies, including audio.
Sling TV’s growth has slowed dramatically as the competitive landscape for live TV streaming services has heated up. Despite this, the Dish -owned streaming service remains ahead of rivals in terms of subscriber count – largely due to it being first to market with streaming TV. Dish said today it closed out the year with 2.417 million Sling TV subscribers. That puts it ahead of AT&T’s DirecTV Now, which ended 2018 with 1.6 million subscribers.
It’s also more than newcomers like YouTube TV and Hulu with Live TV. The latter topped 1 million subscribers this past fall. YouTube TV doesn’t report its numbers, but had an estimated 800,000 subscribers as of last July. It’s likely neck-and-neck with Hulu Live TV at this point.
Dish reported its Sling TV numbers as a part of its Q4 2018 earnings, which also indicated that Sling TV is nowhere near making up for the subscriber loss from Dish’s satellite TV service. The company lost 1.125 million satellite TV subscribers during its fiscal 2018, up from the 995,000 it lost the year prior.
The company closed out the quarter with 12.32 million total pay TV subscribers, including 9.90 million Dish TV subscribers and 2.42 million Sling TV subscribers, it said.
In addition to the increased competition from other streaming services and a price increase, Dish’s carriage disputes have also impacted Sling TV.
The company no longer carries Univision on Dish or Sling TV. Plus, HBO and Cinemax left Dish and Sling TV on October 31, due to a dispute with the premium networks’ new owner, AT&T.
The move to drop HBO and Cinemax had already taken its toll on Sling TV in Q3, when Dish reported a net add of only 26,000 new Sling TV subscribers for the quarter.
Unfortunately for Sling TV, these moves may not be enough. And things won’t get better in 2019 as a number of new streaming video services compete for customers’ dollars – like those from Time Warner, Apple, and Disney.
Prosecutors have brought charges against a former Air Force officer for allegedly spying for Iran, the Justice Department confirmed Wednesday.
Monica Witt, a former Air Force counter-intelligence officer, is accused of defecting to Iran in 2013, after leaving the military in 2008 after more than a decade’s service and later working as a defense contractor.
Prosecutors said the officer, who according to the unsealed indictment had the highest level of top secret clearance, disclosed the details of a highly classified intelligence-gathering program that involved an intelligence operation against “a specific target.” Witt is also accused of disclosing the true identity of a U.S. intelligence officer to the Iranian Revolutionary Guard, which conducts the country’s cyber-operation, after she stopped working for the U.S. government.
Witt, a former Texas resident, first traveled to Iran in 2012 to attend a conference, which is where prosecutors allege she was recruited.
FBI executive assistant director for national security Jay Tabb said the indictments follow “years of investigative work,” adding that her alleged actions “could cause serious damage to national security.”
A previously released FBI missing persons report asking for information regarding Monica Elfriede Witt. (Image: FBI/supplied)
An arrest warrant was issued for Witt, who is still believed to be in Iran.
Prosecutors also charged four other Iranian nationals accused of working for the Revolutionary Guard — Mojtaba Masoumpour, Behzad Mesri, Hossein Parvar and Mohamad Paryar — with cyber-offenses relating to targeting U.S. government agents who once worked with Witt.
Prosecutors said the “skilled cyber actors” targeted Witt’s former colleagues with malware, which allowed the hackers to spy on the victims’ webcams and keystrokes.
Officials said that the hackers “tested its malware and gathered information from target computers or networks, and sent spearphishing messages to its targets.” In one case, prosecutors said the hackers created a fake Facebook account of a former colleague of Witt’s, which resulted in several of the targets to accept the fake account’s friend requests.
The government also issued sanctions against two companies, including New Horizon, which sets up the annual conference which Witt attended, for providing financial and technical support to the Revolutionary Guard. Treasury Secretary Steven Mnuchin said it took the action “against malicious Iranian cyber actors and covert operations that have targeted Americans at home and overseas as part of our ongoing efforts to counter the Iranian regime’s cyber attacks,” specifically attempts to install malware to compromise the computers of U.S. personnel.
A long-time London-based entrepreneur re-surfaces today with the launch of Numan a new kind of subscription business, with a rather unusual approach to a very old problem.
Sokratis Papafloratos (pictured) is one of the more ‘serial of serial’ European entrepreneurs. He was one of the first investors in Calm.com the mindfulness sleep and meditation site and app which recently attained Unicorn status. He also founded TrustedPlaces, the UK’s earliest and oldest local reviews site, which was Acquired by Yell Group Plc; family-photo-sharing platform, Togethera (which shuttered) and Secret Escapes, one of the UK’s first members-only travel company.
Papafloratos is now turning his attention to a tricky subject for men: erectile dysfunction (ED).
The startup is backed by, it says, a group of top-tier investors, led by Vostok New Ventures (who led the round for Voi and are significant investors in Babylon Health). ‘Health’ is where we get some more clues.
If you are familiar with businesses like Birch Box which sends women clothes on a subscription basis, you’ll be familiar with Numan. This online platform will aim to promote accessible medical remedies for ED whilst also building a brand and story-telling around health issues affecting men’s self-esteem and the lifestyle choices they make that might affect their condition.
While the early strategy will involve pharmaceuticals on subscription, the longer term play, says Papafloratos, will be the offer of direct-to-consumer medical products to help control the symptoms of ED, along with online support from healthcare professionals. It will also involve editorial content to help men and women understand the issue. Eventually, this could be a sort of “Babylon Health for Men’s Health”. But for now, the MVP involved drugs and content.
In case you are unaware, Erectile Dysfunction is the inability to get and maintain an erection, a condition that appareently affects two-thirds of men in the UK at any one time. It has been linked to mental health and lifestyle factors, such as anxiety, stress, alcohol and relationships. That means Numan will automatically have an audience, perhaps embarrassed by their predicament, who probably would rather look online for solutions than go for therapy or medical help.
Treatment will be offered in the form of generic solutions, such as Sildenafil and soon Tadalafil, and Viagra Connect. All medication provided by Numan is licensed for sale in the UK by the Medicines and and Healthcare products Regulatory Agency (MHRA), which also oversees the authorisation of the numan.com to sell medicines online.
By selecting a treatment on the Numan homepage, consumers will be able to create an account, complete a short questionnaire covering symptoms and medical history. Then a member of Numan’s qualified clinical team will assess their suitability for the treatment. Once approval is granted, a prescription is created and the tablets are shipped and delivered to within 48 hours.
Numan next plans to expand its health and grooming offering to include skin and hair treatment for men.
Papafloratos says: “We’re not just providing an online pharmacy though. We’re putting real emphasis on providing you with the knowledge you need to make the right decisions for you. So we’re releasing The Book of Erections – an in-depth guide on how your erections come about, or sometimes don’t and what you can do about it. We’re also supporting that with in-depth information on our blog.”
He says the startup ran a survey of 1,000 men and 1,000 women in the UK earlier this year and found that from the men who reported having erectile dysfunction symptoms, only 42% sought help on the issue.
Slack has become a critical communications tool for many organizations. One of the things that has driven its rapid success has been the ability to connect to external enterprise apps inside of Slack, giving employees what is essentially a centralized workhub. This ability has led to some unintended consequences around formatting issues, which Slack addressed today with two new tools, Block Kit and Block Kit Builder.
Block Kit lets developers present dense content in a much more visually appealing way, while Block Kit Builder is a prototyping tool for building more attractive apps inside Slack. The idea is to provide a way to deliver content inside of Slack without having to do work-arounds to make the content look good.
Before and after applying Block Kit. Screen: Slack
Bear Douglas, who is Slack’s director of developer of relations, says developers have been quite creative up until now when it comes to formatting, but the company has been working to simplify it. Today’s announcement is the culmination of that work.
“Block Kit makes it easier for people to quickly design a customized app in Slack. We’ve launched a no-code builder that will let people design the messages that they show inside Slack,” she explained.
She said, that while this tool is really designed for people with some programming or Slack admin-level knowledge, the ultimate goal is to make it easy enough for non-technical end users to build apps in Slack, something that is on the road map. What enhancing these tools does, however, is show people just what is possible inside of Slack.
“When people see Block Kit in action, it is illuminating about what can be done, and it helps them understand that it doesn’t just need to be your communications center or [something that pings you] when your website blows up. You can actually get work done inside of Slack,” she said.
One other advantage of using Block Kit is that apps will display messages consistently, whether you are using the web or mobile. Prior to having these tools, work-arounds might have looked fine on the web, but the spacing might have been off on mobile or vice versa. Block Kit lets you design consistent interfaces across platforms.
Among the tools Slack is offering, none is actually earth shattering, but in total they provide users with the ability to format their content in a way that makes sense using common design elements like image containers, dividers and sections. They are also offering buttons, drop-down menus and a calendar picker.
Both of these tools are available starting today in the Block Kit hub.
“These new investments will give us the capacity to hire tens of thousands of employees, and enable the creation of more than 10,000 new construction jobs in Nebraska, Nevada, Ohio, Texas, Oklahoma, South Carolina and Virginia,” Google CEO Sundar Pichai writes today. “With this new investment, Google will now have a home in 24 total states, including data centers in 13 communities. 2019 marks the second year in a row we’ll be growing faster outside of the Bay Area than in it.”
