It is the one-year anniversary of Russia’s latest invasion of Ukraine. On the battlefield AI is assisting both sides in the fight.
Members representing 60 countries gathered in The Hague to discuss the legal and ethical consequences of AI’s use in the military.
AI might not take your job any time soon, but companies are already using it to help them decide who to lay off.
That’s according to a November Capterra survey of 300 US human resources leaders, which found that 98% of respondents plan to use software and algorithms to help them make any layoff decisions in 2023.
While many companies have access to a wide range of employee data — including information on employee attendance, pay, and experience — the HR leaders said “skills” and “performance” data would be most likely to be used in a layoff decision, with 70% of the leaders saying each of these would be considered.
A million here, times a million there. Pretty soon you’re talking about big numbers. So Nvidia claims for its AI accelerating hardware in terms of the performance boost it has delivered over the last decade and will deliver again over the next 10 years.
The result, if Nvidia is correct, will be a new industry of AI factories across the world and gigantic breakthroughs in AI processing power. It also means, ostensibly, AI models one million times more powerful than existing examples, including ChatGPT, in AI processing terms at least.
But the computing power necessary for a company to adopt in-house AI capabilities is enormous, and that’s where Nvidia’s new service offering comes in. Dubbed “DGX Cloud,” Nvidia is offering an AI supercomputer accessible to its customers via a web browser. The company partnered with various cloud providers, including Microsoft, Google, and Oracle, to launch the service.
“Nvidia AI as a service offers enterprises easy access to the world’s most advanced AI platform, while remaining close to the storage, networking, security and cloud services offered by the world’s most advanced clouds,” Huang explained.
“Nvidia AI is essentially the operating system of AI systems today,” Huang also said.
As the power of AI grows, we need to have evidence of its sentience. That is why we must return to the minds of animals by Kristin Andrews & Jonathan Birch + BIO.
Quantum computers are highly energy-efficient and extremely powerful supercomputers. But for these machines to realize their full potential in new applications like artificial intelligence or machine learning, researchers are hard at work at perfecting the underlying electronics to process their calculations. A team at Fraunhofer IZM are working on superconducting connections that measure a mere ten micrometers in thickness, moving the industry a substantial step closer to a future of commercially viable quantum computers.
With the extreme computing power they promise, quantum computers have the potential to become the driving force for technological innovations in all areas of modern industry. By contrast with the run-of-the-mill computers of today, they do not work with bits, but with qubits: No longer are these units of information restricted to the binary states of 1 or 0.
With quantum superposition or entanglement added, qubits mean a great leap forward in terms of sheer speed and power and the complexity of the calculations they can handle. One simple rule still holds, though: More qubits mean more speed and more computing power.
Posted in business, robotics/AI
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Synthetic speech and voice cloning startup Resemble AI has introduced an “audio watermark” to tag AI-generated speech without compromising sound quality. The new PerTh Perceptual Threshold) Watermarker embeds the sonic signature of Resemble’s synthetic media engine into a recording to mark its AI origin regardless of future audio manipulation, yet subtle enough that no human can hear it.
Audio Watermarking
Visual watermarking hides one image within another, invisible without a computer scanner in the case of particularly high-security documents. The same principle applies to audio watermarks, except it’s a very soft sound that people won’t notice but encoded with information that a computer could decipher. The concept isn’t new, but Resemble has leveraged its audio AI to make PerTh more reliable without compromising the realism of its synthetic speech creation.
Quiet sounds can be obliterated easily in most cases, but Resemble figured out a way to hide its identification tones within the sounds of speech. As people talking is the point of Resemble’s services, the audio watermark is much more likely to come through an edit unscathed. Resemble takes advantage of how humans tend to focus on specific frequencies and how louder sounds can hide quieter noises that are close in frequency. The combination masks and protects the watermark sound from humans noticing or being able to extract the audio watermark. Resemble’s machine learning model can determine where to embed the quiet sonic tag, generate the appropriate sound, and put it in place. The diagram below illustrates how the watermark hides in plain sight, or sound in this case.
The brain signals successfully directed the robodogs toward a number of locations that the human controller picked “telepathically” by imagining them.
The Australian military is reportedly testing a unique artificial intelligence (AI) “brain robotic interface” to control “robodogs” synced with troopers’ minds.
The army “is exploring the use of brain signals to control robotic and autonomous systems.” reads the video description.
