There are some markets with complex problems, and high domain expertise, but the experience with deep learning frameworks is low. Among these are industrial use cases—from optimization and control of physical devices to other complex problems in large-scale logistics. These are areas where simulations have traditionally been key to optimize and control machines or logistics systems, but implementing an intelligent approach—one that learns through experience via data and domain expert input—can add value.
This specific set of use cases is where machine learning startup Bons.ai is putting its research into practice—and it seems to be gaining traction with $13.6 million raised so far and one of their users, Siemens, as both an investor and end user. The company’s co-founder and CEO, Mark Hammond, tells The Next Platform that although for now their early customers are getting quite a bit of one-on-one attention with moving their optimization and control problems into the company’s platform, the goal is to bring simulation data for physical and logistics problems directly to the platform with its custom-built compiler that whittles down to TensorFlow via their Inkling programming language for true self-service machine learning and deep learning for non-experts.
Hammond, who has a background in computer science and neuroscience, which he has put into practice at startup Numenta and Microsoft, says his company wants to do for machine learning what databases did for data. “In the same way databases gave users a new language like SQL to program the intent for many types of business questions with the ability to specify structures and leave low level management to the technology, we want to do the same for AI.”
Verily Life Sciences, the high-profile Google offshoot, has lost the scientist who led its search for better ways to prevent, detect, and treat mental illness — the latest in a string of top executives who have left the company after a short tenure.
Dr. Thomas Insel, former head of the National Institute of Mental Health, joined the Silicon Valley startup with fanfare in December 2015. He was lured, he wrote at the time, by the Google philosophy to seek “a 10x impact on hard problems. I am looking forward to a 10x challenge in mental health.”
The Snapdragon 660 mobile platform is now shipping while the Snapdragon 630 mobile platform will begin shipping towards the end of this month. Qualcomm has outed the Snapdragon 660 and 630 mobile processors (sorry, platforms) which will bring machine learning smarts and advanced photography skills to mid-range smartphones.
The NHL playoffs are in full swing and as the players focus on the Stanley Cup, SFU Beedie student Cole Gawenda is already looking ahead to next season, and how statistics on American Hockey League (AHL) players might impact the better-known NHL—including its first NHL client team, the Washington Capitals.
The Capitals are one of eight teams currently in this season’s second round of playoffs.
Data from the SFU team at HockeyData Inc. may assist with future planning as the team goes forward. “Our process involves tracking every individual player’s events based on time and location throughout a game,” explains Gawenda, operations manager. “We track each player’s performance and provide this data to the team, which allows them to gain a greater understanding of players in the American Hockey League.”
This morning Amazon announced a new product: The Echo Show. This brings the entire lineup of Amazon’s Alexa-enabled hardware to include the Echo, Echo Dot, Amazon Tap, Echo Look, and now the Echo Show. Impressive for only ~2 years since the initial product launched. This is the first in the lineup to include a touch screen display, offering new capabilities and some exciting potential. Below are some of our favorite features and capabilities we think you should know about!
NVIDIA CEO Jen-Hsun Huang announced the new NVIDIA Tesla V100, the most advanced accelerator ever built.
From recognizing speech to training virtual personal assistants to converse naturally; from detecting lanes on the road to teaching autonomous cars to drive; data scientists are taking on increasingly complex challenges with AI. Solving these kinds of problems requires training exponentially more complex deep learning models in a practical amount of time.
This report, created by analyzing millions of job postings using advanced technology, divides Data Science and Analytics roles into 6 broad categories, and answers many questions, including cities, industries, job roles with most growth.
Biotia, a startup offering microbial surveillance for hospitals, is a joint venture between researchers at Weill Cornell Medicine and Cornell Tech. Founded through the Runway Startup program at the Jacobs Technion-Cornell Institute at Cornell Tech, Biotia is led by experts in genomics, bioinformatics and applied evolutionary biology: Chris Mason, Ph.D., Weill Cornell Medicine associate professor of physiology and biophysics and of computational genomics in the HRH Prince Alwaleed Bin Talal Bin Abdulaziz Al-Saud Institute for Computational Biomedicine; and Niamh B. O’Hara, Ph.D., a researcher and startup postdoc at the Jacobs Technion-Cornell Institute. The Jacobs Institute gives financial and mentoring support to Ph.D.s in tech fields who have recently graduated and are interested in launching a tech-related startup. Biotia has already received some funding and anticipates Series A funding in mid-2018.
A system called VALCRI should do the laborious parts of a crime analyst’s job in seconds, while also suggesting new lines of enquiry and possible motives
For more than a year now since we enhanced our timeline to show the best Tweets for you first, we have worked to improve the underlying algorithms in order to surface content that is even more relevant to you.
Today we are explaining how our ranking algorithm is powered by deep neural networks, leveraging the modeling capabilities and AI platform built by Cortex, one of our in-house AI teams at Twitter. In a nutshell: this means more relevant timelines now, and in the future, as this opens the door for us to use more of the many novelties that the deep learning community has to offer, especially in the areas of NLP (Natural Language Processing), conversation understanding, and media domains.
Doctors often struggle to choose the best dose of a drug for each patient — the dose that worked for patient A isn’t enough for patient B, or it is way too much for patient C. The response is governed by a host of factors, including genetics, age, body size, the use of other medications, the presence of diseases and the development of drug tolerances.
Now, Stanford researchers are developing new technology to help deliver an optimal, personalized drug dose. Using their drug delivery system, they were able to automatically administer chemotherapy at the desired concentration in mice, as reported today in Nature Biomedical Engineering.
Nigerian health officials won’t have to rely on flawed, decade-old census data when they plan deliveries of the measles vaccine next year. Instead, they will have access to what may be the most detailed and up-to-date population map ever produced for a developing country. Created by the Bill & Melinda Gates Foundation in Seattle, Washington, and delivered to Nigerian officials on 1 May, the map is based on a detailed analysis of buildings in satellite imagery and more than 2,000 on-the-ground neighbourhood surveys.
It is one of several projects that are leveraging remote-sensing data and modern computer-learning algorithms to chart human settlements around the globe with unprecedented precision. Researchers hope that these data will enable better management of public health, infrastructure and natural resources — and improve planning for emergencies. This is especially true in developing countries, where census estimates are notoriously unreliable and outdated.
In just minutes online, you leave a rich digital trail behind. Data scientist Michal Kosinski developed a powerful algorithm that collects all those digital crumbs and creates a profile of you so intimate it might even surprise your spouse. [video, 13:34]
The Merlin Bird ID mobile app has been launched and, thanks to machine-learning technology, can identify hundreds of North American species it “sees” in photos. The app was developed by Caltech and Cornell Tech computer-vision researchers in partnership with the Cornell Lab of Ornithology and bird enthusiasts. Once it is downloaded on a mobile device, Merlin Bird ID can go anywhere bird watchers go—even places without cell service or Wi-Fi.
“When you open the Merlin Bird ID app, you’re asked if you want to take a picture with your smartphone or pull in an image from your digital camera,” says Merlin project leader Jessie Barry at the Cornell Lab. “You zoom in on the bird, confirm the date and location, and Merlin will show you the top choices for a match from among the 650 North American species it knows.”
That’s a knowledge gap Stanford biomedical data scientist Dennis Wall, PhD, wants to fill — not just in the United States but also around the world. A new paper, published online in JMIR Public Health & Surveillance, explains how Wall and his team created GapMap, an interactive website designed to crowdsource the missing autism data. They’re now inviting people and families affected by autism to contribute to the database.
Oxford, England There is a need for fresh, serious thinking about how AI will reshape business. A three-part discussion series this spring aims to bring new voices to the conversation. May 18 at 6 p.m., Said Business School [free, registration required]
Bloomington, IN Monday, July 24, at the University of Indiana. Talk and build amongst the communities working on developing standards for open science sUAS [unmanned drones] data. [free, registration required]
AMIA invites all informatics professionals and students to participate in an important and unique opportunity to help shape the future of informatics. Survey closes May 24.
The ASA/NCTM Joint Committee on the Curriculum in Statistics and Probability and the ASA’s Education Department encourage students and their advisers to participate in its annual Project Competition (written report). Deadline is June 1.
Digital Humanities Advancement Grants (DHAG) support digital projects throughout their lifecycles, from early start-up phases through implementation and long-term sustainability. Deadline is June 6.
“My student Palash Goyal and I recently finalized a survey on graph embedding techniques, which can be found on arxiv.” … “We released a companion open-source Python library, called GEM (Graph Embedding Methods), which can be found on github.”
