The biggest names in tech are encouraging developers to build products for their app ecosystem. File photo taken in 2015 shows an illustration of an iPhone held up in front of the Apple logo. SAN FRANCISCO -- Like a dressed-down awards season, Apple's WWDC conference concludes a three-month developer season. But will it end with a bang, as the Academy Awards do for the film industry? It began with Microsoft's Build in March and continued with Facebook's F8 show in April and Google I/O in May. The quartet of tech behemoths are sharing their latest-and-greatest with developers to entice them to create new apps for products and services for the fall and beyond.

The department of applied mathematics of CentraleSupelec has an immediate opening at the level of assistant professor in the areas of statistics, and / or machine learning and /or data mining. Successful applicants should have an outstanding track record & publications and should will to contribute to the further expansion of the department in one of the above areas both from research (establish an independent research group) and teaching view point. Research-wise the applicant could also benefit from the established collaboration between CentraleSupelec and Inria which is the French National Institute for Research in computer science and applied mathematics. Successful applicants should hold a PhD in mathematics, computer science or engineering in an area like statistics, machine learning or data mining or a related one and should be able to demonstrated an outstanding record in research and teaching. Applications should be mailed electronically to the chairs of the hiring committee: - Professor Nikos Paragios, nikos.paragios@ecp.fr - Professor Erick Herbin, Chair of the department, erick.herbin@ecp.fr

The Machine Learning (AppStat) group of the Linear Accelerator Laboratory (LAL) is seeking a postdoctoral researcher for working at the interface of machine learning and experimental high-energy particle physics. The researcher will work with the dynamic interdisciplinary group which organized the HiggsML challenge, including Cecile Germain and Isabelle Guyon (LRI), and Balázs Kégl and David Rousseau (LAL) Some of the ongoing themes are deep learning for next-generation high-resolution pixel calorimeters, including the systematic uncertainties in training ML models for discovery, and budgeted learning for real-time triggers. All themes include the development of state-of-the-art ML solutions that can make a real difference in both the design and in the data analysis phases of ongoing and future large-scale physics experiments (e.g., ATLAS, LHCb, the future ILC). The candidate will also be part of the Paris-Saclay Center of Data Science and will be expected to participate in the mission of the center through its activities (eg, RAMPs, software carpentry, thematic days). We are accepting candidates both from data science (ML, statistics, signal processing) and from high-energy physics, given that the candidate is ready to cross the disciplinary aisles.

Domestic companies are coming up with a series of new services that leverage the latest in drone technology. MicroAd Inc., a Tokyo-based online advertising company, has unveiled a service called Sky Magic to produce sound-and-light extravaganzas. Drones illuminated with LED lights can project logos, words, shapes and pictures in spaces above large-scale events. At its roll-out event in Chiba in April, five drones flew in a formation depicting an inverted image of Mt. Fuji as a live shamisen performance was held in front of an audience of some 1,300.

FILE - In this June 10, 2013, file photo, Eddy Cue, Apple senior vice president of internet software and services, talking about the new voices of Siri virtual assistant during the keynote address of the Apple Worldwide Developers Conference in San Francisco. Apple's Siri made a big splash when the wisecracking digital assistant debuted in 2011. But as its competitors jockey to build intelligent "chat bots" and voice-controlled home systems capable of more challenging artificial-intelligence feats, Siri at times no longer seems cutting edge. On Monday, June 13, 2016, Apple is expected to demonstrate how much smarter Siri can get as it kicks off its annual software conference.

In the movie Transcendence, Johnny Depp plays Dr Will Caster, a researcher in artificial intelligence at Berkeley trying to build a sentient computer. Stuart Russell is Will Caster's real life equivalent. He works on artificial intelligence at the University of California at Berkeley, and is co-author of the definitive textbook on AI. He has also been very vocal about the risks of research in AI succeeding. Earlier this year, Google's DeepMind taught a computer program to play a wide variety of Atari video games at a superhuman level in a matter of hours.

Siri is expected to expand beyond the iPhone and iPad to third-party apps and Macs, a move designed to hike the usefulness and IQ of Apple's personal digital assistant. Analysts who cover Apple predict an expanded role for Siri will be one highlight of the Apple Worldwide Developers Conference, which begins Monday in San Francisco. Apple did not respond to a request for comment. The Cupertino, California company has a big job ahead. Even though Siri was first to bat among digital assistants, it has limited utility and risks putting Apple in second-tier status when it comes to the make-or-break technology of the moment: artificial intelligence and natural-language learning that can simulate human conversation.

Since making its first public appearance last October, Sharp Corp.'s humanoid robot smartphone, RoBoHoN, has created a lot of buzz. But the eye-catching 19.5-cm-tall robot, which can walk, talk and dance but still works as a phone, has also left many people wondering why a phone and a robot should be bundled together, and what Sharp's long game is. As it turns out, Sharp is dead serious about the project. Officials say the firm thinks a robot phone could be the next big thing -- in fact, as big as the smartphone boom. The company is even envisioning a science fiction-like future in which everyone will carry his or her own robot phone that doubles as a personal assistant.

For nearly 30 years, the industry has talked about the coming of one big interconnected network of plants, supply chains, enterprises and technology that creates a digital-lean-manufacturing nirvana. While we're well on our way to reaching that mountain-top of just-in-time delivery and zero waste, a risk-adverse culture has slowed the implementation of machine learning. Up until this point, machine learning in the Industrial Internet has focused on optimizing at the machine level. We have access to a ton of data about machine function and productivity that we have used to run our machines at full capacity for as long as possible and predict many maintenance issues. But now it's time to take the next step and start looking at network-wide efficiency.

Matt Krisiloff is in a small, glass-walled conference room off the lobby of Y Combinator's office in San Francisco's South of Market neighborhood, shouting distance from some of the country's wealthiest startups, many of which Y Combinator has nurtured and helped fund. Krisiloff, who manages the operations of the tech incubator's program for very early-stage companies, is explaining why it is committed to investing an amount said to be in the tens of millions of dollars in a venture that is guaranteed never to make a penny. It's the simplest business model conceivable: hand thousands of dollars over to individuals in return for nothing, no strings attached. Krisiloff insists he and his Y Combinator colleagues can't wait to get started giving away the money. "This could be really transformative," he says. "It may help change how humans, society, and technology all operate together in the future."