As streaming has taken over, the AV1 codec has come up as a way to save bandwidth and improve quality going forward. According to a mention from the folks over at Synaptics, YouTube and Netflix apparently have plans to require AV1 at some point in the future.
There’s no date attached to this right now, but Synaptics mentions that AV1 will be required by YouTube and Netflix, the two biggest streaming platforms in the world, at some point. Why mention? It comes as Synaptics announces its VideoSmart VS640 SoC that supports hardware decoding of the AV1 standard.
Google is already starting to require Android TV devices to ship with support for AV1 decoding.
AV1 has been the subject of much interest in recent years — at least as far as interest in obscurely technical topics like video encoding goes. And it's also gaining support from many of the most prominent players in the tech space, with YouTube and Netflix both adding at least partial support on their platforms.
7 marketplace platforms, including StockX, Faire, and virtual goods seller Genies, that experts predict could follow Poshmark to IPO
Finding a good deal is harder than it looks: Even when the discount seems steep, you’re usually left wondering if what you’ve unearthed is truly an excellent deal or just a dud wrapped in overhyped sales lingo. Price drops on refurbished gear—gently used tech and appliances that are resold following a manufacturer tune-up—only complicate the matter. Refurbs are almost always sold at a significant discount (and more often than not, they work just as well as brand-new gear), but the idea of dropping a lot of cash on previously owned items can feel a bit unsettling.
The impulse to shy away from refurbs is understandable: The deal was difficult enough to find in the first place; toss in the possibility of a refurb that could potentially arrive damaged, in shoddy condition, or otherwise nonfunctional, and it becomes that much more daunting. The Wirecutter Deals team has done the research for you, and before we post the deal, a refurb has to meet our specific criteria:
While many eyes, including mine, were on CES this week, today, I wanted to talk about a tech announcement that may have flown under the radar in the run-up to the holidays. I’ve been following Synaptics for some time now and watched it progress from Synaptics 1.0 (PC trackpads, etc.) to 2.0 (mobile, fingerprint readers) and now, what it calls Synaptics 3.0—a much more focused Synaptics, expanding aggressively into new, rapidly growing markets such as consumer IoT and automotive. Under new CEO Michael Hurston (who took the reins in 2019), Synaptics has been able to break out of the stagnation it fell into in the mid-2010s. While Synaptics has long had an impressive portfolio of IP—1,800+ patents and counting—it struggled to develop effective roadmaps and engage constructively with customers. A big part of the company’s comeback is due to its renewed focus and diversification into IoT, the success of which was evident in Synaptics’ recent Q1 earnings results. And that is the category where today’s news falls: the introduction of a new offering, the Katana Platform, an SoC for low power edge AI. Let’s take a look at what Katana is all about.
When you’re in the processor business, you’re also in the compiler business. Like it or not, inventing a new CPU or MCU with its own instruction set means you’re also on the hook for its entire software-development toolchain. In fact, a lot of “chip companies” employ more programmers than circuit designers.
And you thought inventing a new computer was hard.
That was the tall order facing Eta Compute. One of many, in fact. The small startup took on all sorts of self-imposed burdens. It invented a new MCU for AI inferencing. It invented a new low-power circuit design methodology it called DIAL (delay-insensitive asynchronous logic). It developed the chip’s compiler from scratch. Then it reinvented DIAL to create CVFS (continuous voltage and frequency scaling), which it then used to create an entirely new second-generation chip, the ECM3532. Then it had to redo the compiler for the new chip. And, when all of that was done, it had to go beat the bushes looking for customers who wanted an ultra-low-power MCU for “ML at the edge” from a new company nobody had ever heard of.
Surprisingly, all of that worked, and Eta Compute now has a handful of happy paying customers. But it was too much effort to be sustainable, so the company has made a strategic pivot. It’s now a “software and systems company,” meaning MCU development has halted and its second generation of chips won’t have any offspring. It’s the end of the line for Eta Compute’s hardware roadmap, but a new life for its compiler.
Researchers in Switzerland and the Netherlands have used event driven image sensors to improve the safety of a multi-rotor autonomous drone.
Once a motor fails, a drone can rotate uncontrollably, making navigation and stabilisation very difficult. Larger drones use GNSS satellite receivers to try to regain control of the system, but this is not practical for smaller aircraft.
“When one rotor fails, the drone begins to spin on itself like a ballerina,” said Davide Scaramuzza, head of the Robotics and Perception Group at UZH and of the Rescue Robotics Grand Challenge at NCCR Robotics, which funded the research. “This high-speed rotational motion causes standard controllers to fail unless the drone has access to very accurate position measurements.”
Instead, the technique developed by the researchers combine data from a standard camera with an event-driven camera sensor that only responds to changes in an image. These event driven, neuromorphic or spiking neural network sensors are being commercialised by companies such as Prophesee in France and Opteran in the UK. The team plans to release the technology as open source.
While the coronavirus pandemic captured the world’s attention in 2020, the climate crisis was also massively destructive, with ramifications including an extended wildfire season in California and tens of thousands of deaths from air pollution and rising temperatures in the United States alone.
The global response to the climate crisis has been muted and insufficient according to international scientists and regulatory agencies, but with revenues and bottom lines at stake, businesses are increasingly changing their ways to adjust for the climate crisis.
More than half of consumers — 57% — say they are willing to change their purchasing behavior “to help reduce negative environmental impact,” according to a study of 18,980 consumers in 29 countries conducted by the National Retail Federation with the IBM Institute for Business Value (IBV) and published in 2020.
Charleston Business Magazine celebrates another year of honoring the region’s most influential people. The selection of our 50 individuals is a result of staff research and community nominations.
Take a look inside to see who made the list. And this year, we’re adding five members to our Hall of Fame who have continued to make a lasting difference in the Lowcountry.
Two years ago, the computer vision community was abuzz with anticipation for a new type of sensor that promised a revolution in speed and efficiency.
These new sensors are called event cameras, and also know as dynamic vision sensors (DVS) or neuromorphic cameras.
Yet two years later, many of us are now wondering why event cameras seem to have joined Spinal Tap in the “Where Are They Now?” file.
The idea behind event cameras is compelling: a camera that works very much like the human eye. In doing so, it can react quicker, under more circumstances, while transmitting much less data. But before we can understand how an event camera works, let’s first review traditional cameras.
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