Arm takes machine learning mainstream with neural processing units


Arm aims to take machine learning to mainstream and low-end devices with the launch of its new neural processing units (NPUs). The company is unveiling the Ethos-N57 and Ethos-N37 NPUs, which it will license to chipmakers who can integrate it into their products. The idea is to extend the range of Arm machine learning (ML) processors to enable artificial intelligence (AI) applications in mainstream devices. The company also unveiled the Mali-G57 graphics processing unit (GPU). This is the first mainstream Valhall architecture-based GPU, delivering 1.3 times better performance over previous generations.

Hitachi Vantara CTO on quantum, data ethics, and public trust


When quantum computing moves from the theoretical world into the applied space it threatens to break apart the accepted modus operandi of much of the technology industry, something Hubert Yoshida, the CTO of Hitachi Vantara is keenly aware of. Search giant Google made a surprise announcement that it had reached quantum supremacy last month, raising serious questions about how organisations can manage and secure data in the future. Nowehere is this more important than in the domain of cryptography. Where once it could take hundreds of years to crack encryption methods with traditional computing, quantum computing techniques could lower that to just seconds. "We have to keep one step ahead and find different ways of doing encryption in the face of new technologies," Yoshida, told Computerworld, speaking during the Hitachi Next conference at the MGM Grand, Las Vegas, last week.

The Station: Volvo evolves, Skip trips and touchscreen tech – TechCrunch


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DepthAI: Myriad X Based Platform for AI Development - Robotic Gizmos


Here is another kit for those of you serious about AI and depth, and tracking applications. DepthAI is built around the Myriad VPU. It takes care of depth, AI, and feature tracking, so the included Raspberry Pi Computer 3B module stays at 0% CPU use. DepthA has 3 onboard cameras, standard Pi header, Raspberry Pi Compute Module connector, and other convenient ports for your projects. You can find out more about it here.

The best gaming laptops of 2019

USATODAY - Tech Top Stories

If you make a purchase by clicking one of our links, we may earn a small share of the revenue. However, our picks and opinions are independent from USA TODAY's newsroom and any business incentives. Buying a gaming machine is no longer as challenging as a game of Tetris. Thanks to smaller chips and lighter hardware, now you can buy a powerhouse in laptop form that will optimize gaming experience without having to piece together the hardware yourself. Gaming laptops have made PC gaming so much more accessible, and you can easily find machines with high-resolution displays and the latest graphics cards without breaking the bank. We've done the hard work for you, researching and testing out the top options on the market. After weeks of testing we think the Alienware M15 with an Nvidia GeForce 2070 is the best overall for people who want a high-performance machine. If you need something a little more budget-friendly, the Acer Nitro 7 can handle just about any current game as well for under $1,000.

Computers Gone Wild--6 Movies to Help You Ponder Our Quantum Future


How do you explain quantum computing? Think of that vintage telephone at the General Store on Petticoat Junction. Put it next to your iPhone. Every day, it seems like there is news of yet another breakthrough in computing. Technology experts debate exactly when we will all have quantum computers instead of Echo Dots, but the day is coming.

Quantum Information and AI


"The tantalizing promise of quantum computers is that certain computational tasks might be executed exponentially faster on a quantum processor than on a classical processor. A fundamental challenge is to build a high-fidelity processor capable of running quantum algorithms in an exponentially large computational space. Here, we report using a processor with programmable superconducting qubits to create quantum states on 53 qubits, occupying a state space 253 1016. Measurements from repeated experiments sample the corresponding probability distribution, which we verify using classical simulations. While our processor takes about 200 seconds to sample one instance of the quantum circuit 1 million times, a state-of-the-art supercomputer would require approximately 10,000 years to perform the equivalent task. This dramatic speedup relative to all known classical algorithms provides an experimental realization of quantum supremacy on a computational task and heralds the advent of a much-anticipated computing paradigm." It is fascinating to consider what will happen next in the intersection of quantum information and artificial intelligence. It is also hard to tell where it will lead, perhaps a new computing paradigm?

Rahko raises £1.3M seed from Balderton for quantum machine learning tech – TechCrunch


There remains a problem with the race to create a quantum computer, which is that experiments in this area can be extremely error-prone. Rahko is a new U.K. startup that thinks it can address this problem with what's known as "Quantum machine learning." It's now raised £1.3 million ($1.6 million) in a seed round led by Balderton Capital, a rare move for a VC that normally only comes in at a Series A level. Joining the round is AI Seed and angel investors Charles Songhurst (former Microsoft head of Corporate Strategy), Tom McInerney (founder, TGM Ventures), John Spindler (CEO, Capital Enterprise) and James Field (CEO, LabGenius). Rahko says it is building "quantum discovery" capabilities for chemical simulation, which could enable groundbreaking advances in batteries, chemicals, advanced materials and drugs.

Python, PyGame and Raspberry Pi Game Development - Programmer Books


Gain the basics of Python and use PyGame to create fast-paced video games with great graphics and sounds. You'll also learn about object oriented programming (OOP) as well as design patterns like model-view-controller (MVC) and finite state machines (FSMs). Python, PyGame and Raspberry Pi Game Development teaches you how to use Python and PyGame on your computer. Whether you use Windows, macOS, Linux, or a Raspberry Pi you can unleash the power of Python and PyGame to create great looking games. Included in the text are complete code listings and explanations for "Bricks," "Snake" and "Invaders"– three fully-working games.

General Micro Systems (GMS) Launches S1202-XVE, the Industry's Smallest and Lightest Video Server with Artificial Intelligence for Rugged Military & Industrial Applications


WIRE)--General Micro Systems (GMS), the rugged C4ISR mobile systems and servers company, today announced the industry's smallest, lightest and most SWaP-C-optimized workstation, display and general-purpose graphics processing unit (GPGPU) artificial intelligence (AI) algorithm and video processor. At only seven pounds and 9.8 inches x 5.4 inches x 2.3 inches, the ultra-rugged S1202-XVE Peacock III enables the near real-time video processing of large amounts of high-quality images, video or sensor data for immediate and accurate analysis--right on the battlefield. This powerful processing performance makes the system ideal for military applications in harsh environments such as airborne reconnaissance, autonomous vehicles, wide-body C4ISR platforms, multi-console displays and other areas of modern warfare. When equipped with third-party software algorithms, the S1202-XVE compresses, trans-codes, transmits and stores live video and sensor data over IP-based terrestrial or satellite networks with up to 2:1 HEVC compression (compared with AVC) while retaining resolution. The S1202-XVE supports three independent outputs of 4K UHD video, with an additional Nvidia Quadro Pascal GPGPU providing up to eight TFLOPS for algorithm, vector or AI processing in near real time.