An algorithm trained to mimic the Grimm style leads to a new story. “You might call it a form of literary cloning,” says the co-founder of the app that commissioned it.
Source: CNET
More than one member of Congress quizzed CEO Mark Zuckerberg about why his social network had banned the conservative siblings.
Source: CNET
In his second day of Congressional testimony, Democrats wanted to know about privacy. Republicans wanted to hear about Diamond and Silk.
Source: Wired
Congressional hearings with Facebook’s Mark Zuckerberg get lawmakers talking openly this week about regulating how internet companies collect and use consumers’ data.
Source: CNET
HP and Dell grow their PC businesses during a stagnant quarter, market researchers find.
Source: CNET
We’ve trained machine learning systems to identify objects, navigate streets and recognize facial expressions, but as difficult as they may be, they don’t even touch the level of sophistication required to simulate, for example, a dog. Well, this project aims to do just that — in a very limited way, of course. By observing the behavior of A Very Good Girl, this AI learned the rudiments of how to act like a dog.
It’s a collaboration between the University of Washington and the Allen Institute for AI, and the resulting paper will be presented at CVPR in June.
Why do this? Well, although much work has been done to simulate the sub-tasks of perception like identifying an object and picking it up, little has been done in terms of “understanding visual data to the extent that an agent can take actions and perform tasks in the visual world.” In other words, act not as the eye, but as the thing controlling the eye.
And why dogs? Because they’re intelligent agents of sufficient complexity, “yet their goals and motivations are often unknown a priori.” In other words, dogs are clearly smart, but we have no idea what they’re thinking.
As an initial foray into this line of research, the team wanted to see if by monitoring the dog closely and mapping its movements and actions to the environment it sees, they could create a system that accurately predicted those movements.
In order to do so, they loaded up a Malamute named Kelp M. Redmon with a basic suite of sensors. There’s a GoPro camera on Kelp’s head, six inertial measurement units (on the legs, tail and trunk) to tell where everything is, a microphone and an Arduino that tied the data together.
They recorded many hours of activities — walking in various environments, fetching things, playing at a dog park, eating — syncing the dog’s movements to what it saw. The result is the Dataset of Ego-Centric Actions in a Dog Environment, or DECADE, which they used to train a new AI agent.
This agent, given certain sensory input — say a view of a room or street, or a ball flying past it — was to predict what a dog would do in that situation. Not to any serious level of detail, of course — but even just figuring out how to move its body and to where is a pretty major task.
“It learns how to move the joints to walk, learns how to avoid obstacles when walking or running,” explained Hessam Bagherinezhad, one of the researchers, in an email. “It learns to run for the squirrels, follow the owner, track the flying dog toys (when playing fetch). These are some of the basic AI tasks in both computer vision and robotics that we’ve been trying to solve by collecting separate data for each task (e.g. motion planning, walkable surface, object detection, object tracking, person recognition).”
That can produce some rather complex data: For example, the dog model must know, just as the dog itself does, where it can walk when it needs to get from here to there. It can’t walk on trees, or cars, or (depending on the house) couches. So the model learns that as well, and this can be deployed separately as a computer vision model for finding out where a pet (or small legged robot) can get to in a given image.
This was just an initial experiment, the researchers say, with success but limited results. Others may consider bringing in more senses (smell is an obvious one) or seeing how a model produced from one dog (or many) generalizes to other dogs. They conclude: “We hope this work paves the way towards better understanding of visual intelligence and of the other intelligent beings that inhabit our world.”
Source: TechCrunch
Give the internet some credit: people watched hours upon hours of testimony just to get some jokes off.
Source: Wired
With the number of fantasy sports players in North America heading past 60 million, and the industry said to be worth more than $7 billion, fantasy sports games are clearly on the rise. On the web, the two biggest players are FanDuel and DraftKings, which between them control 90 percent of the market. But translating that kind of business into a blockchain world could have even more potential, turning the reward system into a cryptocurrency nirvana.
This is the aim of two blockchain-based startups, No Limit Fantasy Sports and MyDFS. Both have differing models, but both are aiming at the incumbents, which are probably unable to grow much further, and especially after their merger was rejected by regulators.
Now, MyDFS plans to take the fight to the next level, with a $2 million cash injection from investor Frank Fu, managing director at Chinese technology company Meitu, the Chinese photo-sharing platform with 456 million users. He’ll also join as a board advisor to the company.
Fu says the union of gaming and blockchain is inevitable because “blockchain guarantees safe storage of all in-game digital assets” and “smart contracts exclude third parties from the payment process and make transactions fast and safe” by removing the need for a financial intermediary for transactions.
The view is that potential for payment fraud in fantasy sports means the sector is ripe for blockchain technology, which can record every transaction.
MyDFS CEO Viktor Mangazeev believes tokenization and blockchain will make fantasy sports far more “transparent and user-friendly” and will allow players to invest not just in the games, teams and players, but also other players, by earning a share of their winnings. So, in theory, you could hitch your prospects to the best players because of the use of in-game cryptocurrency.
It looks as if blockchain is going to gradually lead to more startups arriving in this arena. Distributed ledger technology could mean a large reduction in transfer times and fees, while affording a more transparent fantasy economy.
Smart contracts could also mean users get their prizes literally as soon as they’ve won games, instead of having to wait for other sites to verify the games. And finally, the use of cryptocurrency (MyDFS uses Ethereum, while No Limit Fantasy Sports uses their own coin called NoLimitCoin) should be able to avoid regulatory issues, at least for now, because the “betting” is not based on fiat currency. That means these sites could reach more global audiences faster.
That said, we will have to wait and see what happens next in terms of regulation and whether these platforms will, in fact, have global appeal after all.
Source: TechCrunch
El responsable de X, la división de proyectos alocados de Alphabet, Astro Teller, explica que esta tecnología necesita enfrentarse a situaciones lo más reales posibles pero con cuidado. Y afirma que muchas veces se ha puesto delante de vehículos sin conductor de la compañía
Source: MIT
Zipline, famosa por su exitoso servicio de entrega de fármacos en África, presenta un nuevo dispositivo aún más rápido. La mejora en el aparato y en todas sus operaciones han multiplicado por 10 el número de entregas diarias. Ahora, la empresa intenta expandirse por todos los rincones del planeta
Source: MIT