The first autonomous robots to deliver packages straight to your front door won't be flying -- they'll be rolling around on six wheels. Starship Technologies, an Estonia-based startup created by two Skype co-founders, Janus Friis and Ahti Heinla, is slated to begin testing its autonomous delivery robot to bring groceries and restaurant takeout to Washington, D.C., homes and businesses this fall. It's the first U.S. municipality to approve ground-based robots to roll around on city sidewalks. Starship hopes to solve the "last mile" problem –– the work of getting packages from the fulfillment center directly to people's homes -- currently done by humans. It's a problem Amazon wants to solve with drones, but the FAA's rules bar drones from flying around humans without an operator in line of sight.

Artificial Intelligence has always been one of the frontiers of computer science research, and it's always important to take a look at the roots of this exciting field. With the death of AI pioneer John McCarthy at the age of 84 being announced, programmers all over the world are publicly mourning over social networks. In additon to founding artificial intelligence programs at both MIT and Stanford, his best known contribution to artificial intelligence research was the Lisp programming language. Lisp stood for "List Processsing," and featured an incredibly elegant programming model. The main data structure in Lisp is, you guessed it, a list.

In this paper we study the problem of recovering a structured but unknown parameter ${\bf{\theta}}^*$ from $n$ nonlinear observations of the form $y_i=f(\langle {\bf{x}}_i,{\bf{\theta}}^*\rangle)$ for $i=1,2,\ldots,n$. We develop a framework for characterizing time-data tradeoffs for a variety of parameter estimation algorithms when the nonlinear function $f$ is unknown. This framework includes many popular heuristics such as projected/proximal gradient descent and stochastic schemes. For example, we show that a projected gradient descent scheme converges at a linear rate to a reliable solution with a near minimal number of samples. We provide a sharp characterization of the convergence rate of such algorithms as a function of sample size, amount of a-prior knowledge available about the parameter and a measure of the nonlinearity of the function $f$. These results provide a precise understanding of the various tradeoffs involved between statistical and computational resources as well as a-prior side information available for such nonlinear parameter estimation problems.

The best part of "Radio Imagination: Artists in the Archive of Octavia E. Butler" is the view it provides into Butler's archive itself. Butler, who died in 2006, was a bestselling Pasadena novelist and the only science fiction writer to win a MacArthur fellowship. She was also African American, and her novels reworked the sci-fi genre with far-reaching insights on race, sex and gender. The exhibition at the Armory Center for the Arts in Pasadena features works by eight artists who were granted access to Butler's archives at the Huntington Library in San Marino. Their responses take a variety of forms, including sound and video as well as photography, drawing and installation.

In May, Google research scientist Douglas Eck left his Silicon Valley office to spend a few days at Moogfest, a gathering for music, art, and technology enthusiasts deep in North Carolina's Smoky Mountains. Eck told the festival's music-savvy attendees about his team's new ideas about how to teach computers to help musicians write music--generate harmonies, create transitions in a song, and elaborate on a recurring theme. Someday, the machine could learn to write a song all on its own. Eck hadn't come to the festival--which was inspired by the legendary creator of the Moog synthesizer and peopled with musicians and electronic music nerds--simply to introduce his team's challenging project. To "learn" how to create art and music, he and his colleagues need users to feed the machines tons of data, using MIDI, a format more often associated with dinky video game sounds than with complex machine learning.

NVIDIA's (NVDA) quarterly revenues have been surging at double-digit rates in the last three quarters and, looking at the guidance for the next quarter, it's clear that the company is expecting the growth rate to continue unabated in the near future. One of the key factors that has added fuel to their engines is NVIDIA's new growth drivers: the data center segment and auto segment. In the most recent quarter, NVIDIA's data center unit reported 151 million in sales, a growth of 109.72% The growth in data center revenues is much higher than other segments, and there are several reasons why this growth can, in fact, continue its breakneck pace for several more quarters. NVIDIA's expertise in the GPU segment has given it a range of must-have products for hyperscale data centers.

"There's a one in a billion chance that this is reality." There is a growing school of thought in the scientific community that we are all living inside a computer simulation designed by a super-advanced civilization. This is not some fringe idea dreamed up by a weed-smoking wackadoodle in a psychedelic VW van. This is mainstream scientific theory. A who's who of world-renown philosophers and physicists spent hours discussing the controversial concept known as the simulation hypothesis at an annual event at the American Museum of Natural History earlier this year.

An Australian man was acquitted Thursday in the murder of a young woman who fell from his balcony two years ago after the two met through the popular dating app Tinder. What, exactly, caused 26-year-old Warriena Wright to plunge 14 stories is not known, but the encounter between the couple -- much of which was captured on an audio tape -- has prompted the question: Are mobile dating apps safe? The answer is complicated, according to dating experts and behavioral psychologists. "These incidents are very rare," said Sameera Sullivan, a relationship expert and psychologist who founded the matchmaking service, Lasting Connections, in 2012. "There's always going to be bad people out there," said Sullivan.

For the last decade, I have worked closely with families who are trying to find the best senior care facility for a loved one. I am fortunate to work in an area (Portland, OR) that offers a plethora of senior housing options, from traditional Retirement Living, Assisted Living, and Memory Care Communities. Portland also boasts an impressive 900 Adult Care Homes (aka Adult Foster Care or Adult Family Homes) for folks who want/ need a smaller family-style setting. People often ask me what I think the future holds for elder care. I suspect this question stems from fears of what their own future holds or (most likely) that they are terrified of facing their later years in the current senior care model (which is becoming quickly outdated by the social and medical needs of the boomer generation).

The fun part about thinking about artificial intelligences (AI) – especially for folks with a dark sense of humor – is that it is possible to assess its impact in the short term, the medium term and the very long term. The humor springs from the fact that the long-term view refers to the end of civilization. Overriding the conversation is the idea that the sophistication and capabilities of AI are growing at a very rapid clip. It was mostly discussed by futurists and screenwriters just a few years ago. Now, it is at the center of many corporate and business functions.