The proof is in the pudding (or in this case, the hiring): JP Morgan is serious about AI – the bank announced yesterday that have hired Manuela Veloso (former head of Carnegie Mellon University’s Machine Learning department) as the company’s first head of artificial intelligence research.
The impact of AI on banking and financial services as a whole cannot be understated…according to a recent FT survey, 17 of the 18 banks they interviewed were already using some form of AI in the front office. For more on how the effects of automation on banking, see this recent Bloomberg article on a Swedish bank’s pilot project for automating jobs.
The UC Berkeley research team has deemed the robot they are building BRETT — that’s the Berkeley Robot for Elimination of Tedious Tasks. Like the Sawyer robots, BRETT is here to learn — and hopefully offer researchers some valuable insight into how we can teach robots how to perform dull and repetitive tasks without a lot of programming.
In this case, the job is picking and placing — a decidedly tedious warehouse task that has become extremely demanding as online retailers like Amazon have put the crunch on logistics companies. In some scenarios, robots are taught to execute the process through human demonstrations. In others, they’re programmed with tens of thousands of computer simulations. BRETT, on the the other hand, is programmed to learn by doing — and correcting its own mistakes.
Chinese artificial intelligence chip maker Cambricon Technologies Corp Ltd has unveiled two new products, a cloud-based smart chip Cambricon MLU100 and a new version of its AI processor IP product Cambricon 1M, at a launching event in Shanghai on May 3rd. “The MLU1000 chip is a milestone and a new starting point for Cambricon, and a benchmark for smart chip,” Chen Tianshi, CEO at Cambricon, wrote in an internal letter.
Cambricon’s MLU100 chip supports cloud-based machine learning, including vision, audio, natural language processing. It can process under complex scenarios, such as with huge amounts of data, multi-tasks, multi-modality and low latency. It can theoretically perform 166.4 trillion times of fixed-point arithmetic per second at maximum, with energy consumption of no more than 110 watts at peak.
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A 180 year-old robot called “The Android Clarinettist,” is scheduled to participate in a museum exhibit called “Robots Love Music” in the Netherlands later
this year. Unfortunately, nobody can find its instrument. The details: Built in 1838, the ‘self-playing’ robot was created to entertain people. For the time, it was an incredibly advanced automaton – it could play the clarinet and finish its performance with a bow to the audience.
The robot was traveling the world with its creator by 1839. Sometime around 1855 it ended up in the US on loan. It’s known to have survived the Barnum Museum fire of 1865, after that it became the property of different private collectors. Somewhere along the way the robot lost its clothes and any hat or wig it once wore.
More importantly, it lost its clarinet.
Yesterday, ServiceNow announced plans to acquire AI startup Parlo in a cash deal scheduled to close later this month. ServiceNow will integrate Parlo’s natural language understanding technology named Broca into its Now platform for business process automation. Broca will make the Now platform better able to understand the nuances of conversational language.
“We are rapidly moving away from structured data such as filling in forms and data fields, towards unstructured interactions with machines such as free-form text, voice and gestures. Our goal is to make every day work interactions simple, accessible and natural for everyone,” ServiceNow VP Pat Casey said in a statement.
Indeed recently released its top 10 list evaluated based on the number of job postings, salaries over $70,000, and consistent growth between 2014 to 2017. Machine learning engineer, full stack developer, and DevOps engineer made up the top three positions. In January, Indeed identified machine learning engineer as one of the top jobs to watch in 2018 due to the increased function AI plays in almost every industry.
“With Canada’s growing tech sector, we’re continuing to see tech jobs dominate,” said Paul D’Arcy, senior vice president at Indeed. “Our top job, machine learning engineer, is vital to one of Canada’s most important emerging fields, artificial intelligence. With such broad applications and rapid advancements, this field is increasingly contributing to the Canadian tech jobs landscape and we expect this to continue in the years to come.”
Su-In Lee was changed by her father’s passing and his sudden cancer. She came back to Seattle from Korea (where her father was) with a new goal: Find a way to help cancer patients get the best treatment possible, even if that only means giving them a little bit more time with their family.
In the past five years, Lee — a professor of computer science and genome science at the UW — has grown that goal into a precision medicine program called MERGE. MERGE uses machine learning along with a patient’s DNA and other health data to predict which treatments will work best to help them fight the disease. Hear Lee’s full story and learn more about precision medicine work in the most recent episode of GeekWire’s Health Tech Podcast.
A surprisingly large proportion of voice-activated devices out there don’t rely on Alexa, Google Assistant or Siri to power their conversational interfaces. Many hardware makers are instead opting to use technology from a startup called SoundHound Inc., which announced it has raised $100M in funding to capitalise on the demand.
The reason behind SoundHound’s impressive growth is that its voice platform, Houndify, offers a white-label alternative to the leading voice assistants. The software enables companies to provide a conversational experience for customers without having to bring another brand such as Amazon.com Inc., Google Inc. or Apple Inc. into the loop.
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