The U.S. Air Force envisions placing laser weapon systems on fighter jets by the mid-2020s. The service is banking on a defense contractor’s SHiELD laser system, a pod-mounted laser that will protect fighters from incoming missiles.
✈ You love badass planes. So do we. Let’s nerd out over them together.
The year is coming to a close and it’s safe to say Elon Musk’s prediction that his company would field one million “robotaxis” by the end of 2020 isn’t going to come true. In fact, so far, Tesla’s managed to produce exactly zero self-driving vehicles. And we can probably call off the singularity too. GPT-3 has been impressive, but the closer machines get to aping human language the easier it is to see just how far away from us they really are.
So where does that leave us, ultimately, when it comes to the future of AI? That depends on your outlook. Media hype and big tech’s advertising machine has set us up for heartbreak when we compare the reality in 2020 to our 2016-era dreams of fully autonomous flying cars and hyper-personalized digital assistants capable of managing the workload of our lives.
Continue reading “Neural’s market outlook for artificial intelligence in 2021 and beyond” »
Intel, in its latest acquisition spree, has acquired Israel-based Cnvrg.io. The deal, like most of the deals in the past, is aimed at strengthening its machine learning and AI operations. The 2016-founded startup provides a platform for data scientists to build and run machine learning models that can be used to train, run comparisons and recommendations, among others. Co-founded by Yochay Ettun and Leah Forkosh Kolben, Cnvrg was valued at around $17 million in its last round.
According to a statement by Intel spokesperson, Cnvrg will be an independent Intel company and will continue to serve its existing and future customers after the acquisition. However, there is no information on the financial terms of the deal or who will join Intel from the startup.
The deal comes merely a week after Intel’s announcement of acquiring San Francisco-based software optimisation startup SigOpt, which it did to leverage SigOpt’s technologies across its products to accelerate, amplify and scale AI software tools. SigOpt’s software technologies combined with Intel hardware products could give it a major competitive advantage providing differentiated value for data scientists and developers.
Military observers said the disruptive technologies – those that fundamentally change the status quo – might include such things as sixth-generation fighters, high-energy weapons like laser and rail guns, quantum radar and communications systems, new stealth materials, autonomous combat robots, orbital spacecraft, and biological technologies such as prosthetics and powered exoskeletons.
Speeding up the development of ‘strategic forward-looking disruptive technologies’ is a focus of the country’s latest five-year plan.
Intel continues to snap up startups to build out its machine learning and AI operations. In the latest move, TechCrunch has learned that the chip giant has acquired Cnvrg.io, an Israeli company that has built and operates a platform for data scientists to build and run machine learning models, which can be used to train and track multiple models and run comparisons on them, build recommendations and more.
Intel confirmed the acquisition to us with a short note. “We can confirm that we have acquired Cnvrg,” a spokesperson said. “Cnvrg will be an independent Intel company and will continue to serve its existing and future customers.” Those customers include Lightricks, ST Unitas and Playtika.
Intel is not disclosing any financial terms of the deal, nor who from the startup will join Intel. Cnvrg, co-founded by Yochay Ettun (CEO) and Leah Forkosh Kolben, had raised $8 million from investors that include Hanaco Venture Capital and Jerusalem Venture Partners, and PitchBook estimates that it was valued at around $17 million in its last round.
Like its key allies, the UK is increasingly reliant on space-based assets for daily life in ordinary civil society and for the perfornance of its military forces. So, the Royal Air Force’s operating domain now extends from the ground to far beyond the atmosphere.
In a lockdown summer of downbeat aviation news, it is perhaps fitting that a highlight was a model aeroplane in a windtunnel. In turbulent times for aerospace, that aircraft is even named after a storm. But in showing some detail of the external shape of the Tempest future fighter, BAE Systems has also emphasised the UK’s determination to ride out the technological, financial and geopolitical hurricanes which are set to shape the national defence challenges of the next few decades.
Those late August images from BAE’s Warton, Lancashire test facility reveal an external profile designed for stealth at Mach 2, to carry a wide range of payloads and to cope with the internal heat from enough onboard electric power to anticipate exotic technologies like laser directed-energy weapons.
Security on the internet is a never-ending cat-and-mouse game. Security specialists constantly come up with new ways of protecting our treasured data, only for cyber criminals to devise new and crafty ways of undermining these defenses. Researchers at TU/e have now found evidence of a highly sophisticated Russian-based online marketplace that trades hundreds of thousands of very detailed user profiles. These personal ‘fingerprints’ allow criminals to circumvent state-of-the-art authentication systems, giving them access to valuable user information, such as credit card details.
Our online economy depends on usernames and passwords to make sure that the person buying stuff or transferring money on the internet, is really the person they are saying. However, this limited way of authentication has proven to be far from secure, as people tend to reuse their passwords across several services and websites. This has led to a massive and highly profitable illegal trade in user credentials: According to a recent estimate (from 2017) some 1.9 billion stolen identities were sold through underground markets in a year’s time.
It will come as no surprise that banks and other digital services have come up with more complex authentication systems, which rely not only on something the users know (their password), but also something they have (e.g. a token). This process, known as multi-factor authentication (MFA), severely limits the potential for cybercrime, but has drawbacks. Because it adds an extra step, many users don’t bother to register for it, which means that only a minority of people use it.
Machine learning (ML) is making incredible transformations in critical areas such as finance, healthcare, and defense, impacting nearly every aspect of our lives. Many businesses, eager to capitalize on advancements in ML, have not scrutinized the security of their ML systems. Today, along with MITRE, and contributions from 11 organizations including IBM, NVIDIA, Bosch, Microsoft is releasing the Adversarial ML Threat Matrix, an industry-focused open framework, to empower security analysts to detect, respond to, and remediate threats against ML systems.
During the last four years, Microsoft has seen a notable increase in attacks on commercial ML systems. Market reports are also bringing attention to this problem: Gartner’s Top 10 Strategic Technology Trends for 2020, published in October 2019, predicts that “Through 2022, 30% of all AI cyberattacks will leverage training-data poisoning, AI model theft, or adversarial samples to attack AI-powered systems.” Despite these compelling reasons to secure ML systems, Microsoft’s survey spanning 28 businesses found that most industry practitioners have yet to come to terms with adversarial machine learning. Twenty-five out of the 28 businesses indicated that they don’t have the right tools in place to secure their ML systems. What’s more, they are explicitly looking for guidance. We found that preparation is not just limited to smaller organizations. We spoke to Fortune 500 companies, governments, non-profits, and small and mid-sized organizations.
Our survey pointed to marked cognitive dissonance especially among security analysts who generally believe that risk to ML systems is a futuristic concern. This is a problem because cyber attacks on ML systems are now on the uptick. For instance, in 2020 we saw the first CVE for an ML component in a commercial system and SEI/CERT issued the first vuln note bringing to attention how many of the current ML systems can be subjected to arbitrary misclassification attacks assaulting the confidentiality, integrity, and availability of ML systems. The academic community has been sounding the alarm since 2004, and have routinely shown that ML systems, if not mindfully secured, can be compromised.
Just a matter of time.
In a new report, the International Energy Agency (IEA) says solar is now the cheapest form of electricity for utility companies to build. That’s thanks to risk-reducing financial policies around the world, the agency says, and it applies to locations with both the most favorable policies and the easiest access to financing. The report underlines how important these policies are to encouraging development of renewables and other environmentally forward technologies.
☀️ You love renewable energy. So do we. Let’s nerd out over it together.
Jointly issued by the Chinese Communist Party and the State Council on Sunday, the measures targeting the tech sector are an important part of Beijing’s 2020–2025 plan for the city, which include pilot reforms in areas from finance and energy to education and transport.
Beijing’s plan doubles down on hopes that Shenzhen will become a global leader in technology and finance and a showcase for Xi’s vision of an ideal Chinese society.
