Archive for January 2017
The father of Pac-Man has died.
Masaya Nakamura founded the Japanese video game company Namco in 1955. Pac-Man was designed by Namco engineer and videogame maker Toru Iwatani, and went on sale in 1980.
Pac-Man is estimated to have been played more than 10 billion times, making it the world’s most successful coin-operated arcade game according to Guinness World Record.
As Bloomberg reported, the idea for Pac-Man’s design came from the image of a pizza with a slice carved out. Who knew?!
Nakamura was said to have chosen the word “Pac,” or “pakku” in Japanese, to represent the sound of the Pac-Man muching its prey.
It’s a sound I know I’ll never, ever forget.
IBM has announced that its PowerAI distribution for popular open source Machine Learning and Deep Learning frameworks on the POWER8 architecture now supports the TensorFlow 0.12 framework that was originally created by Google.
TensorFlow support through IBM PowerAI provides enterprises with another option for fast, flexible, and production-ready tools and support for developing advanced machine learning products and systems.
As one of the fastest growing fields of machine learning, deep learning makes it possible to process enormous datasets with millions or even billions of elements and extract useful predictive models. Deep learning is transforming the businesses of leading consumer Web and mobile application companies, and it is quickly being adopted by more traditional business enterprises as well.
IBM developed PowerAI, enterprise distribution and support for open-source machine and deep learning frameworks used to build cognitive applications. PowerAI helps reduce the complexity and risk of deploying these open source frameworks for enterprises on the Power architecture.
PowerAI is tuned for performance. It offers enterprise support on IBM Power Systems S822LC for HPC platforms used by thousands of developers in commercial, academic and hyperscale systems environments. These Power systems are built with IBM’s POWER8 with NVIDIA NVLink processor that is linked via the high-speed NVLink interface to NVIDIA’s Tesla Pascal P100 GPU accelerators. The CPU to GPU and GPU to GPU NVLink connections give a performance boost to deep learning and analytics applications.
In addition, deep learning and other machine learning techniques are being deployed across a wide range of industry sectors including banking, the automotive industry and retail.
IBM also added the Chainer deep learning framework to the latest release of PowerAI.
PowerAI now includes CAFFE, Chainer, TensorFlow, Theano, Torch, NVIDIA DIGITS, and several other machine and deep learning frameworks and libraries and is available for download from https://www.ibm.com/us-en/marketplace/deep-learning-platform.
Apple Inc. is set to join the Partnership on AI, an artificial intelligence research group that includes Amazon.com Inc., Alphabet Inc.’s Google, Facebook Inc. IBM, and Microsoft Corp., according to Bloomberg.
Despite having initiated somewhat of a lead on the rest of the industry with the introduction of the Siri virtual assistant in 2011, poor Siri seems to have been held back in AI school.
The Partneship on AI is a tech industry body that was established to agree on best practices in the use of artificial intelligence. It was formed in September, with part of its brief to make recommendations in the areas of ethics, fairness, inclusivity, privacy and trustworthiness
Apple’s admission into the group could be announced as soon as this week, according to people familiar with the situation.
9to5 Mac suggests Apple’s reluctance to join may have been prompted by secrecy concerns. In addition to its ethics focus, the group has an emphasis on collaboration between researchers working for different companies.
Siri, fingers crossed…Siri, did you hear me?…SIRI!???!!!!
AppleInsider recently reported that Apple’s latest iOS 10.3 beta release addresses the concerns of people already worrying about losing their precious AirPods.
I’d be worried too at $160 a pop (and $69 replacement per earbud).
Some clever third-party developer launched an app earlier this month that uses AirPod’s Bluetooth signal strength to track down the missing buds, and soon thereafter Apple removed that app from the App Store.
Also in the new iOS 10, Apple is working to crack down on those reminders we iOS users get to rate programs in the App Store. The new policy will include a mechanism that limits developers to seeking reviews and ratings up to three times per year.
In the meantime, I have my own short review to share of my new Apple Watch. I wrote two years ago in February 2015 how I had made an appointment to go into my local Apple store and check out the latest device. I liked it, but knew it was first generation, and I’ve been burned enough buying the first time around that I figured I’d wait for the second.
Ironically, I ended up buying a Series 1 anyway, only two years later. Why? Cost, for one, but also because the Series 2 doesn’t bring that many new advantages over the Series 1 other than the full waterproofing and embedded GPS. And, of course, because the software has been updated a couple of generations since then (it’s all about the software, bay-bay).
My impressions thus far?
First, it was extremely easy to set up.
Second, it’s been very easy to learn how to use thus far.
Third, as so many people will tell you, the notifications (and haptic sensor) are probably the “killer app,” making it very easy to glance at your wrist to check for new messages or get that text from your significant other.
But that’s just a first impression…let me get a few more days under my belt and I can probably tell you more.
Just don’t ask me to review your latest app over and over again in the meantime. : )
In a Wall Street Journal article published earlier today, Red Hat CEO Jim Whitehurst suggested “the incorporation of machine learning as an element of software is about to soar.”
He told the CIO Journal that currently only about 1% of software developers currently employ machine learning in their work, but that that percentage would rise to about one third of all developers over the next few years.
On a similar note, just last week the MIT Technology Review reported that the Google Brain AI research group also had software design a machine learning system used to benchmark software that processes language.
MIT wrote in its story, entitled “AI Software Learns to Make AI Software,” that:
If self-starting AI techniques become practical, they could increase the pace at which machine-learning software is implemented across the economy. Companies must currently pay a premium for machine-learning experts, who are in short supply.
– via MIT Technology Review
But don’t throw away all the humans just yet. The Google Brain researchers indicated that it took:
800 high-powered graphics processors to power software that came up with designs for image recognition systems that rivaled the best designed by humans.
– via MIT Technology Review
Paul Bunyan, meet Babe the Blue AI Ox.
IBM Security today announced plans to acquire Agile 3 Solutions, a developer of software used by the C-Suite and senior executives to better visualize, understand and manage risks associated with the protection of sensitive data.
The addition of Agile 3 Solutions’ capabilities to IBM Security’s portfolio adds an intuitive tool to improve C-Suite decision making as businesses prepare to defend themselves against cybercrime.
As cybersecurity has become a board-level issue, there is a growing need for the C-suite and the Board to understand their security posture through the lens of business risk, not just the technical security data and metrics.
Business leaders must be equipped to make risk-based decisions and prioritize investments toward the cybersecurity readiness and resilience. In fact, Gartner predicted that “by 2017, 80% of IT risk and security organizations will report metrics to non-IT executive decision makers; however, only 20% will be considered useful by the target audience.”
Agile 3 Solutions is a San Francisco-based, privately held company that provides business leaders with a comprehensive, business-friendly dashboard and intuitive data risk control center to help uncover, analyze, and visualize data-related business risks.
Financial terms of the deal were not disclosed and the transaction is expected to close within several weeks.
For more information about Agile 3 Solutions, go to http://www.ibm.com/security/announce/agile3/
If you keep seeing a bunch of ads for Nests and Google Pixel smartphones and other Google products atop your Google search results, the WSJ explains that’s because Google’s purposefully hawking those products on its own inventory.
These days, Google often pushes its growing list of hardware products, from Pixel phones to Nest smart thermostats, in the top ad spot above its search results.
– via WSJ
The Journal conducted an analysis and found that ads for products sold by Google and its sister companies appeared in the most prominent spot in 91 percent of 25,000 recent searches related to such items. In 43 percent of searches, they report, the two top ads both were for Google-related products.
Some specific examples: Google searches for “phones” almost always began with three consecutive ads for Google’s Pixel phones. And all 1,000 searches for “laptops” started with a Chromebook ad. Ninety-eight percent of searches for “watches” presented ads for Android smartwatches.
The WSJ shared its analysis with Google in mid-December, and apparently, many of the ads disappeared. For a week, before they began to reappear the week of December 22.
The innuendo? Is Google using its dominant search share to give its products an edge over competitors, who are also customers of Google?
Google says not, that when it bids on search ads in auctions, other advertisers are charged as if it wasn’t bidding. But online-marketing executives and analysts say Google’s ads can still affect the price, placement and performance of its customers’ ads, writes the Journal.
Duck Duck go, anyone?