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Archivo del Autor: Belen De Leon

Nintendo says Switch won't have a Virtual Console — here's how you'll get your retro fix – CNET

Want a library full of retro Nintendo games? Sounds like you’ll have to piece it together yourself.
Source: CNET

Walmart ends grocery partnership with Uber – Roadshow

The change comes soon after Uber said it’s eliminating its on-demand delivery service called UberRush.
Source: CNET

Reese's Peanut Butter Cups only follows one person on Instagram – CNET

And it makes so much sense.
Source: CNET

BotChain wants to put bot-to-bot communication on the blockchain

Increasingly we are going to be having bots conducting business on a company’s behalf. As that happens, it is going to require a trust mechanism to ensure that bot-to-bot communication is legitimate. BotChain, a new startup out of Boston wants to be the blockchain for registering bots.

The new blockchain, which is built on Ethereum, is designed to register and identify bots and provide a way for companies to collaborate between bots with auditing capabilities built in. BotChain has the potential to become a standard way of sharing data between bots in a trusted way.

The idea is to have an official and sanctioned place for companies to register their bots securely. As the organization describes it, “BotChain offers bot developers, enterprises, software companies, and system integrators the critical systems, standards, and means to validate, certify, and manage the millions of bots and billions of transactions powered by AI.

Photo: allanswart

The company was created by the team at Talla, a bot startup in Cambridge, but the goal is to open this up to much larger community of partners and expand. In fact, early partners include Gupshup, a platform for developers and Howdy.ai, B2B enterprise bot developers along with Polly, CareerLark, Disco (formerly Growbot), Zoom.ai, and Botkeeper.

BotChain is the brainchild of Rob May, who is CEO at Talla. He was formerly co-founder and CEO at Backupify, which was sold to Datto in 2014. He recognized that as bot usage increases, there needed to be a system in place to help companies using bots to exchange information, and eventually even digital currencies to complete transactions in a fully digital context.

May believes that blockchain is the best solution to build this trust mechanism because of the ledger’s nature as an immutable and irrefutable record. If the entities on the blockchain agree to work with one another, and the other members allow it, there should be an element of confidence inherent in that.

He points to other advantages such as being decentralized so that no single company can control the data on the blockchain, and of course nobody can erase a record once it’s been written to the chain. It also provides a way for bots to identify one another in an official way and for participating companies to track transactions between bots.

Talla opened this up to a community of users because it wants BotChain to be a standard way for bots to exchange information. Whether that happens or not remains to be seen, but these types of projects could be important building blocks as companies look for ways to conduct business confidently, even when there are no humans involved.

BotChain has raised $5 million USD in a private token sale to institutional investors such as Galaxy Digital, Pillar, Glasswing and Avalon, according to the company.

In addition, they will be conducting another token pre-sale starting this Friday to raise additional funds from community stakeholders. “This token sale is a way to give [our community] access. Purchasing these tokens allows users to start registering their assets and create chains of immutable records of what their machines have done,” May explained. He said the company expects to raise $20 million this year from stakeholder token sales.

You can learn more about Botchain from this video:


Source: TechCrunch

Google goes all-in on artificial intelligence, renames research division Google AI

With Google’s I/O developer conference kicking off later today, Google is setting the scene for what it expects to be one of the big themes of the event: artificial intelligence. Today, the company rebranded the whole of its Google Research division as Google AI, with the old Google Research site now directing to a newly expanded Google AI site.

Google has over the years worked on a wide variety of other computing pursuits beyond AI, and all of that content will continue to exist within that new site, the company said. But the move signals how Google has increasingly focused a lot of its R&D on breaking new ground across the many facets of AI specifically, from technologies like computer vision, natural language processing, and neural networks, through to applications across virtually any and every business that Google currently and potentially touches, such as video, search and mobile apps, but also healthcare, automotive applications and other verticals.

That’s not just Google reflecting how the wider world of tech is evolving; it’s also a measure of how much Google has influenced it.

“From computer vision to healthcare research to AutoML, we have increasingly put emphasis on implementing machine learning techniques in nearly everything we do at Google,” writes Google’s Christian Howard in a post announcing the change. “Our research has been core to the development and integration of these systems into Google products and platforms. To better reflect this commitment, we’re unifying our efforts under “Google AI”, which encompasses all the state-of-the-art research happening across Google.”

Google seems to imply that further non-AI research will also be housed in the new AI hub, although it’s not really clear how much support and interest there will be for more work in other fields, or if everything now will need to have an AI angle to be progressed. (We’re asking and will update with a response when and if we get it.)

There is some interesting wider context for the rebranding. Just earlier today, Facebook also announced that one of its own research labs, its VR-focused Oculus Research, would be renamed the Facebook Reality Lab (notably no “virtual” in the name). Microsoft actually led the charge nearly two years ago when it recast its own Microsoft Research as Microsoft AI+Research — but it hasn’t (yet?) dropped the Research part of that name.

One big takeaway, I think, is that companies are trying to bring more of their own branding and more application focus into their quasi-academic research groups.

This could be happening here, too. Renaming Google Research into Google AI is a specific change that brings a division whose name might have previously had more general and academic connotations (“research”) into one that is now named much more specifically, and with an end product in mind (“AI”).

It’s a shift that could signify how the company is trying to reorient staff to move away from research for the sake of it, and towards more practical applications.

In the current race for talent and more business opportunities in the next generation of computing, Google is keeping its eye on the AI prize.

 


Source: TechCrunch

Amazon's Ring app let you report package-stealing neighbors – CNET

And maybe puppy-thieving delivery drivers?
Source: CNET

Former Medicare chief Andy Slavitt formally launches Town Hall Ventures to invest in healthcare

Town Hall Ventures launches today as the latest venture investment firm to take a stab at transforming the woefully broken U.S. health care market through technology.

What Town Hall has that many other firms trying to invest in healthcare technology don’t is a group of founders who have spent time in the trenches of the American healthcare system.

The firm is led by Andy Slavitt, the former Administrator of the Center for Medicaid and Medicare Service and the group executive vice president of Optum . Joining Slavitt are Trevor Price, the founder of Oxeon Holdings, an executive search and investment firm focused on life sciences, and David Whelan, the managing general partner of Oxeon Ventures — the predecessor to Town Hall.

Basically, it seems like Oxeon’s sort of spinning out its venture operations into a separate fund and has brought on Slavitt as a new top investor to manage things and add his years of knowledge working with the U.S. government’s healthcare system to the mix.

“Identifying talented entrepreneurs and helping them through the painstaking process of building a great company is something we are passionate about,” said Trevor Price, in a statement. “We believe we will see more entrepreneurs whose missions are to serve the tens of millions of people whose lives can be improved by innovations that allow them to receive the absolute best quality of care, whether being treated at home and/or in other comfortable and low-cost settings.”

While billions of venture dollars are heading towards the healthcare problem here in the U.S., the problems our system of services faces are so large — 120 million Americans spend around $1.2 trillion on health care — that there’s plenty of room for a number of competitors.

Joining the three founding partners are David Mishkin, a former director at Oxeon Partners, who will serve as the firm’s investment director; Natalie Davis, who worked with Slavitt as a senior advisor at CMS; and Lauren Robb, an investment associate who previously worked for Slavitt’s former company, Optum.

 

“As a nation we have significant health care infrastructure serving healthy populations while lower-income communities go underserved, leading to vastly poorer health outcomes,” said Slavitt. “We are at the beginning of a wave of innovation serving Medicare and Medicaid populations. Town Hall is being formed to help lead this massive and necessary shift. The answers are not always traditional; they involve investments in underlying systemic issues as well as innovative approaches that improve people’s health and well-being.”

The firm already has a few interesting investments under its belt — some through the portfolio created by Oxeon Partners.

According to a statement, portfolio companies include:

  • Cityblock Health, Inc., a startup created with Alphabet’s Sidewalk Labs to provide primary care, behavioral health, and human services for cities (and an Oxeon portfolio company);
  • Somatus, Inc., which is focused on creating new models of care for chronic kidney patients using technology;
  • Welbe Health, LLC  a medical and social services provider for seniors who qualify for PACE;
  • Aetion, Inc., an Oxeon portfolio company that sells real-world analytics and evidence to help biopharma companies and payers better understand how drugs work.

The pitch for founders is the staffing network that Town Hall can tap for young companies starting out to tackle huge problems in a massive market, according to executives who have worked with the firm.

“Without Town Hall and the resources and expertise they bring to bear, our goal of transforming care for urban and low-income populations would be moving far slower. In a short time, they have helped us roll out services in our first community, hire a first-class leadership team, and prepare ourselves for the daunting set of challenges that often substantially slow market entry in new health care organizations,” said Iyah Romm, the CEO of Cityblock Health, in a statement. “As a first-time entrepreneur, Town Hall surrounded me with a group of experienced leaders and operators across regulatory, management, fundraising, and technology unparalleled in health care,”

 

 


Source: TechCrunch

XNOR raises $12M for its cloud-free, super-efficient AI

Between Microsoft Build and Google I/O, there are probably more people saying “AI” this week than any previous week in history. But the AI those companies deploy tends to live off in a cloud somewhere — XNOR puts it on devices that may not even be capable of an internet connection. The startup has just pulled in $12 million to continue its pursuit of bringing AI to the edge.

I wrote about the company when it spun off of Seattle-based, Paul Allen–backed AI2; its product is essentially a proprietary method of rendering machine learning models in terms of operations that can be performed quickly by nearly any processor. The speed, memory, and power savings are huge, enabling devices with bargain-bin CPUs to perform serious tasks like real-time object recognition and tracking that normally take serious processing chops to achieve.

Since its debut it took $2.6 million in seed funding and has now filled up its A round, led by Madrona Venture Group, along with NGP Capital, Autotech Ventures and Catapult Ventures.

“AI has done great,” co-founder Ali Farhadi told me, “but for it to become revolutionary it needs to scale beyond where it is right now.”

The fundamental problem, he said, is that AI is too expensive — both in terms of processing time and in money required.

Nearly all major “AI” products do their magic by means of huge banks of computers in the cloud. You send your image or voice snippet or whatever, it does the processing with a machine learning model hosted in some data center, then sends the results back.

For a lot of stuff, that’s fine. It’s okay if Alexa responds in a second or two, or if your images get enhanced with metadata over a period of hours while you’re not paying attention. But if you need a result not just in a second, but in a hundredth of a second, there’s no time for the cloud. And increasingly, there’s no need.

XNOR’s technique allows things like computer vision and voice recognition to be stored and run on devices with extremely limited processing power and RAM. And we’re talking Raspberry Pi Zero here, not just like an older iPhone.

If you wanted to have a camera or smart home type device in every room of your home, monitoring for voices, responding to commands, sending its video feed in to watch for unauthorized visitors or emergency situations — that constant pipe to the cloud starts getting crowded real fast. Better not to send it at all.

This has the pleasant byproduct of not requiring what might be personal data to some cloud server, where you have to trust that it won’t be stored or used against your will. If the data is processed entirely on the device, it’s never shared with third parties. That’s an increasingly attractive proposition.

Developing a model for edge computing isn’t cheap, though. Although AI developers are multiplying, comparatively few are trying to run on resource-limited devices like old phones or cheap security cameras.

XNOR’s model lets a developer or manufacturer plug in a few basic attributes and get a model pre-trained for their needs.

Say you’re the cheap security camera maker; you need to recognize people and pets and fires, but not cars or boats or plants, you’re using such and such ARM core and camera, and you need to render at 5 frames per second but only have 128 MB of RAM to work with. Ding — here’s your model.

Or say you’re a parking lot company and you need to recognize empty spots, license plates, and people lurking suspiciously. You’ve got such and such a setup. Ding — here’s your model.

These AI agents can be dropped into various code bases fairly easily and never need to phone home or have their data audited or updated, they’ll just run like greased lightning on the platform. Farhadi told me they’ve established the most common use cases and devices through research and feedback, and many customers should be able to grab an “off the shelf” model just like that. That’s Phase 1, as he called it, and should be launching this fall.

Phase 2 (in early 2019) will allow for more customization, so for example if your parking lot model becomes a police parking lot model and needs to recognize a specific set of cars and people, or you’re using proprietary hardware not on the list. New models will be able to be trained up on demand.

And Phase 3 is taking models that normally run on cloud infrastructure and adapting and “XNORifying” them for edge deployment. No timeline on that one.

Although the technology lends itself in some ways to the needs of self-driving cars, Farhadi told me that they aren’t going after that sector — yet. It’s still essentially in the prototype phase, he said, and creators of autonomous vehicles are currently trying to prove the idea works fundamentally, not trying to optimize and deliver it at lower cost.

Edge-based AI models will surely be increasingly important as the efficiency of algorithms improves, the power of devices rises, and the demand for quick-turnaround applications grows. XNOR seems to be among the vanguard in this emerging area of the field, but you can almost certainly expect competition to expand along with the market.


Source: TechCrunch

Your Smartphone Choice Could Determine If You'll Get a Loan

European retailers are using digital footprints to help determine credit-worthiness, according to a new study.
Source: Wired

Uber Unveils the Flying Taxi It Wants to Rule the Skies

The catamaran-like electric concept is the sort of vehicle Uber wants to integrate into a flying taxi network—it just needs other people to build the thing.
Source: Wired

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