At first glance launching a new social app may seem as sensible a startup idea as plunging headfirst into shark-infested waters. But with even infamous curtain-ripper Facebook now making grand claims about a ‘pivot to privacy’ it’s clear something is shifting in the commercial shipping channels that contain our digital chatter.
Whisper it: Feeds are tiring. Follows are tedious. Attention is expiring. There’s also, of course, the damage that personal digital baggage left out in the open can wreak long after the fact of a blown fuse or fleeting snap.
Public feeds have become vehicles of self-promotion; carefully and heavily curated — which of course brings its own peer pressures to keep up with friends’ lux exploits and the influencer ‘gram aesthetic that pretends life looks like a magazine spread.
Yet for a brief time, in the gritty early years of social media, there was something akin to spontaneous, confessional reality on show online. People do like to share. That’s mostly been swapped for the polish of aspirational faking it on apps like Facebook-owned Instagram. While genuine friend chatter has moved behind the quasi-closed doors of group messaging apps, like Facebook-owned WhatsApp (or rival Telegram).
If you want to chat more freely online without being defined by your existing social graph the options are less mainstream friendly to say the least.
Twitter is genuinely great if you’re willing to put in the time and effort to find interesting strangers. But its user growth problem shows most consumers just aren’t willing (or able) to do that. Telegram groups also require time and effort to track down.
Also relevant in interest-based chat: Veteran forum Reddit, and game chat platform Discord — both pretty popular, though not in a way that really cuts across the mainstream, tending to cater to more niche and/or …Read More
One of Elon Musk’s stealthier endeavors is set to become a lot less stealthy tonight, with a presentation set for 8 PM PT (11 PM ET) streaming live from its website in which we’ll learn a lot more about Neuralink, the company Musk founded in 2017 to work on brain control interfaces (BCIs) and essentially part of his larger strategy to help mitigate the risks of AI and enhance its potential benefits.
Here’s what we do know about Neuralink already: Its initial goal, at least as of two years ago, was to figure out how brain interfaces could be helpful in alleviating the symptoms of chronic medical conditions, including epilepsy. This goal will involve the development of “ultra high bandwidth brain-machine interfaces to connect humans and computers,” which is the only formal description Neuralink provides of its overall mission on its own website.
In a post on Wait Buy Why back when the company first broke cover, we got a lot more in-depth background about what problem Musk wants to solve and why. Summarized, Neuralink’s mission is very much on trend with Musk’s other ventures, in that it hopes to help humans avoid something he perceives as an existential threat in order that we may survive, thrive and I guess come up with other potential existential threats for him to also then solve.
Ultimately, Neuralink seems to be aiming well beyond its initial exploration of medical technology, which was really just a way to potentially get testing faster with a practical application that’s easier to work with in terms of rules and regulators. Musk’s goal, per the Wait But Why explainer, is actually to eliminate the “compression” that happens when we translate our thoughts into language, and then into input via keyboard, mouse, etc. before actually transmitting it to a …Read More
Researchers associated with Memorial Sloan Kettering Cancer Center and medical tech and computational pathology startup Paige have published a new article in the peer-reviewed medical journal Nature Medicine detailing its artificial intelligence-based detection system for identifying prostate cancer, skin cancer and breast cancer, which the company says achieves “near-perfect accuracy.” The tech described in the article, which employs deep learning trained on a data set of almost 45,000 slide images taken from more than 15,000 patients spanning 44 countries, is novel in that it can eschew the need to curate data sets for training first, which greatly decreases cost and time required to build accurate AI-based diagnostic tools.
Last February, Paige announced $25 million in Series A funding and a partnership with Memorial Sloan Kettering Center (MSK) to gain access to one of the largest single repositories of pathology slides in the world. MSK is also home to the lab of Dr. Thomas Fuchs, Paige’s co-founder and chief scientific officer, and possibly the world’s foremost authority in computational pathology.
Paige’s approach uses much larger data sets than are typically employed in AI-based diagnostics, but without the tight curation that focuses other efforts much more narrowly on specific types of cancer diagnostics. The result, according to the company, is not only better performance, but also a resulting system that is much more generally applicable.
Next up for Paige is to commercialize its technology, which is something it’s already pursuing. The work described in the article published in Nature Medicine has already been employed in technology currently under review by the FDA, albeit for a different final application than the ones described in the study published by the magazine.Read More
The companies aren’t disclosing the financial terms, but as part of the transaction, Vungle has also reached a settlement with founder Zain Jaffer, who filed a wrongful termination lawsuit against the company earlier this year.
(Update: Multiple sources with knowledge of the deal said that the acquisition price was around — or north of — $750 million. One of those sources also said it was an all-cash transaction.)
“As a best-in-class performance marketing platform, Vungle represents a key growth engine for the mobile app ecosystem,” said Blackstone principal Sachin Bavishi in a statement. “Our investment will help deliver on the company’s tremendous growth potential and we look forward to partnering with management to extend Vungle’s strength across mobile gaming and other performance brands.”
Meanwhile, CEO Rick Tallman said the deal will allow the company to “further accelerate Vungle’s mission to be the trusted guide for growth and engagement, transforming how users discover and experience mobile apps.”
Vungle was founded back in 2011, and, according to the acquisition release, it’s currently working with 60,000 mobile apps worldwide, serving more than 4 billion video views per month and working with publishers like Rovio, Zynga, Pandora, Microsoft and Scopely.
Jaffer led Vungle as CEO until October 2017, when he was arrested on charges including performing a lewd act upon a child and assault with a deadly weapon. The charges were ultimately dropped, with the San Mateo County District Attorney’s office stating that it did “not believe that there was any sexual conduct by Mr. Jaffer that evening,” while “the injuries were the result of Mr. Jaffer being in a state of …Read More
While the agility of a Spot or Atlas robot is something to behold, there’s a special merit reserved for tiny, simple robots that work not as a versatile individual but as an adaptable group. These “tribots” are built on the model of ants, and like them can work together to overcome obstacles with teamwork.
Developed by EPFL and Osaka University, tribots are tiny, light and simple, moving more like inchworms than ants, but able to fling themselves up and forward if necessary. The bots themselves and the system they make up are modeled on trap-jaw ants, which alternate between crawling and jumping, and work (as do most other ants) in fluid roles like explorer, worker and leader. Each robot is not itself very intelligent, but they are controlled as a collective that deploys their abilities intelligently.
In this case a team of tribots might be expected to get from one end of a piece of complex terrain to another. An explorer could move ahead, sensing obstacles and relaying their locations and dimensions to the rest of the team. The leader can then assign worker units to head over to try to push the obstacles out of the way. If that doesn’t work, an explorer can try hopping over it — and if successful, it can relay its telemetry to the others so they can do the same thing.
It’s all done quite slowly at this point — you’ll notice that in the video, much of the action is happening at 16x speed. But rapidity isn’t the idea here; similar to Squishy Robotics’ creations, it’s more about adaptability and simplicity of deployment.
The little bots weigh only 10 grams each, and …Read More
Today’s wearables are still designed for the healthy and wealthy, not those who could benefit the most. Medical wearables offer the potential to collect health data and improve health via a combination of real-time AI and expert human intervention. Apple’s announcement of FDA clearance of its Watch for screening for irregular heart rhythms was meant to be groundbreaking. But its medical value right now remains limited and controversial. What will make the promise into reality?
I believe the application that will make wearables medically matter is automated blood pressure monitoring. Blood pressure may not be sexy, but it’s a universally understood measurement and a clinically central one. Your doctor measures your blood pressure every single time you visit. Even those who don’t pay close attention to their health know that high blood pressure increases risk of heart attack and stroke, and lower blood pressure saves lives.
High blood pressure, or hypertension, affects between 30-50% of adult Americans, or 75-120 million people. It’s the No. 1 risk factor in deaths worldwide, and the No. 1 modifiable risk in heart disease and stroke, the top two worldwide causes of death. Despite this, only half of people with high blood pressure are lowering it enough, even with medications. Why? A big reason is lack of information.
Doctors advise everyone at risk to monitor their blood pressure, but few do it often enough, in large part because inflatable blood pressure cuffs, while universal, are uncomfortable and inconvenient. In fact, current medical guidelines recommend automated blood pressure monitoring to more accurately measure your blood pressure, but hardly anyone is willing to use a motorized cuff that squeezes your arm every 30 minutes …Read More
With over-the-top (OTT) changing the way we consume entertainment across devices, most of the media attention is going to the big players trying to elbow their way into the streaming space with big new subscription services and original programming. Less discussed is the suite of technologies that pave the way for those services to connect to their audience and monetize the content.
Okay, it’s true video compression, identity management, analytics, front-end personalization and device-specific experience optimization are not the sexiest topics in the media world. But without those core features and functions, the OTT revolution would be dead in its tracks. And with the big providers focused on content development, user acquisition and business model optimization, development of those technologies is wide open for innovative startups.
As always, entrepreneurs should look for cracks and gaps in the existing processes to find better solutions. Right now, the biggest systemic pains in the emerging OTT ecosystem are around the complexity of the fragmented user experience – having to sign in and out of multiple systems to get to the content we want to watch – and around adapting old mass-audience advertising models to the new era of multi-device, multi-platform, personalized viewing.
Here are three areas where small, nimble startups could make a real contribution to the industry.
Currently the streaming market is divided between ad-supported services and premium-fee subscription models, but that hard division is unlikely to survive the next wave of market disruption. Premium services like Netflix will need to introduce a lower-fee ad-based tier to expand their audience and compete with lower-priced offerings like Disney+. More fundamentally, streamers will need additional …Read More
Earlier this year, at MWC, Microsoft announced the return of its Kinect sensor in the form of an AI developer kit. The $399 Azure Kinect DK camera system includes a 1MP depth camera, 360-degree microphone, 12MP RGB camera and an orientation sensor, all in a relatively small package. The kit has been available for pre-order for a few months now, but as the company announced today, it’s now generally available and shipping to pre-order customers in the U.S. and China.
Unlike the original Kinect, which launched as an Xbox gaming accessory that never quite caught on, the Azure Kinect is all business. It’s meant to give developers a platform to experiment with AI tools and plug into Azure’s ecosystem of machine learning services (though using Azure is not mandatory).
To help developers get started, the company already launched a number of SDKs, including a preview of a body-tracking SDK that is close to what you may remember from the Kinect’s Xbox days.
The core of the camera has more to do with Microsoft’s HoloLens than the original Kinect. As the company notes in its press materials, the Azure Kinect DK uses the same time-of-flight sensor the company developed for the second generation of its HoloLens AR visor. And while the focus here is clearly on using the camera, Microsoft also notes that the microphone array also allows developers to build sophisticated speech solutions.
The company is positioning the device as an easy gateway for its users in health and life sciences, retail, logistics and robotics to start experimenting with using depth sensing and machine learning. We’ve seen somewhat similar dev kits from others, including Microsoft partner Qualcomm, though these devices don’t usually have the depth camera that makes the Kinect DK a Kinect.… Read More
When it comes to applying AI to the world around us, Andrew Ng has few if any peers. We are delighted to announce that the renowned founder, investor, AI expert and Stanford professor will join us onstage at the TechCrunch Sessions: Enterprise show on September 5 at the Yerba Buena Center in San Francisco.
AI promises to transform the $500 billion enterprise world like nothing since the cloud and SaaS. Hundreds of startups are already seizing the AI moment in areas like recruiting, marketing and communications and customer experience. The oceans of data required to power AI are becoming dramatically more valuable, which in turn is fueling the rise of new data platforms, another big topic of the show.
Last year, Ng launched the $175 million AI Fund, backed by big names like Sequoia, NEA, Greylock and SoftBank. The fund’s goal is to develop new AI businesses in a studio model and spin them out when they are ready for prime time. The first of that fund’s cohort is Landing AI, which also launched last year and aims to “empower companies to jumpstart AI and realize practical value.” It’s a wave businesses will want to catch if Ng is anywhere near right in his conviction that AI will generate $13 trillion in GDP growth globally in the next 20 years. You heard that right.
At TC Sessions: Enterprise, TechCrunch’s editors will ask Ng to detail how he believes AI will unfold in the enterprise world and bring big productivity gains to business.
As the former chief scientist at Baidu and the founding lead of Google Brain, Ng led the AI transformation of two of the world’s leading technology companies. Dr. Ng is the co-founder of Coursera, an online learning platform, and founder of deeplearning.ai, an AI …Read More
Arraiy raised $13.9 million according to Crunchbase, most recently a $10 million Series A in March of 2018. Lux Capital and SoftBank Ventures Asia led the round. Lux Capital notably also led Matterport’s Series A back in 2013. In comparison, Matterport has raised about $114 million to date.
Arraiy used AI tech to more seamlessly overlay digital content on physically captured spaces. The company had been firmly focused on changing the way digital effects houses in Hollywood made films. While plenty of computer vision startups were aiming to use AI and AR technologies to bring live Snapchat-like AR functionality to different corners of the web, Arraiy was banking on the high-fidelity world of film, where special effects production is an expensive, time-intensive process.
Arraiy’s founders previously started Industrial Perception, a robotics startup that Google acquired in 2013.
The startup tackling Hollywood special effects and a startup best known for digitizing real estate properties to give potential buyers 3D tours might not seem like the most idyllic pairing, but the acquisition might allow Matterport to expand its ambitions further beyond its real estate customer base.Read More