Security camera maker Wyze will "temporarily" remove its AI-powered person detection feature. Wyze's partner for the feature, Xnor.ai, made the decision to terminate their agreement. In a post on its forums, Wyze explained its agreement with Xnor.ai included a clause allowing the contract to be terminated "at any moment without reason." A reason for the abrupt contract termination has not been provided. AI News has reached out to Xnor.ai for comment but is yet to receive a response.

French startup Foodvisor has raised a $4.5 million funding round after generating 2 million app downloads. Agrinnovation is leading the round and various business angels are also participating. I covered Foodvisor last month, so I'm not going to describe the app once again. In a few words, the startup uses deep learning to enable image recognition to detect what you're about to eat. It can detect the type of food and it also tries to estimate the weight of each item.

By Country (United States; Canada; Mexico and Rest of North America) 6.3.

YOKOHAMA – Nissan is investing ¥33 billion ($303 million) in its flagship auto plant in Tochigi Prefecture in a first rollout of a production system geared toward electric vehicles. Nissan Motor Co. Executive Vice President Hideyuki Sakamoto said Thursday that manufacturing methods must change because vehicles increasingly have both hybrid and electric engines and new parts for connectivity and artificial intelligence services. Sakamoto said the production changes, set to be completed next year, use robotics and sensors to decrease physical stress on assembly-line workers. They are tailored for a workforce increasingly manned by senior workers and women. Among the innovations for Nissan's "intelligent factory" is a powertrain mounting system that allows at least 27 configurations to be installed in one procedure.

Machine learning has been used by scientists in the US to reduce unwanted fluctuations in photon beams from a synchrotron light source. The technique does this by stabilizing the synchrotron's electron beam and offers a way around an important barrier to the development of next-generation facilities. The work was done by Simon Leemann and colleagues at the Lawrence Berkeley National Laboratory (LBNL) in California and could allow emerging analysis techniques that require high beam stability – such as X-ray photon correlation spectroscopy (XPCS) – to be implemented on synchrotons. Synchrotron light sources are extremely useful scientific instruments because they deliver bright, high-quality beams of coherent electromagnetic radiation from infrared wavelengths up to soft X-rays. The light is produced by accelerating electrons in a storage ring using powerful magnets – taking advantage of the fact that an accelerated electron emits electromagnetic radiation.

The global artificial intelligence chipset market size is expected to reach USD 59.2 billion by 2025, according to a new report by Grand View Research, Inc. The artificial intelligence (AI) chipset market is anticipated to expand at a CAGR of 33.6% from 2019 to 2025. An Artificial Intelligence chipset is built on the concept of adding a dedicated component in an electronic device, to execute Machine Learning tasks. In addition, an increased amount of data has led to the need for high-speed processors and faster computing, which is addressed by incorporating Artificial Intelligence into the set of electronic components. For instance, Apple has implemented a neural engine in its A11 Bionic chip's GPU to speed-up the third-party applications.

Researchers at the National Institute of Standards and Technology (NIST) have developed an optical switch that is capable of rerouting light between computer chips within 20 billionths of a second. The new device is faster than any similar devices, and it could be integrated into low-cost silicon chips due to its low voltages. When it redirects light, the chip suffers very low signal loss. The new chip will have big implications for computing, and it will help develop a computer that processes information using light rather than electricity. There are several advantages to using photons in order to transport data including faster travel and energy efficiency.

Cambridge, MA, November 28, 2019 -- Dyno Therapeutics, a biotechnology company pioneering use of artificial intelligence in gene therapy, today announced a publication in the journal Science that demonstrates the power of a comprehensive machine-guided approach to engineer improved capsids for gene therapy delivery. The research was conducted by Dyno co-founders Eric D. Kelsic, Ph.D. and Sam Sinai, Ph.D., together with colleague Pierce Ogden, Ph.D., at Harvard's Wyss Institute for Biologically Inspired Engineering and the Harvard Medical School laboratory of George M. Church, Ph.D., a Dyno scientific co-founder. AAV capsids are presently the most commonly used vector for gene therapy because of their established ability to deliver genetic material to patient organs with a proven safety profile. However, there are only a few naturally occurring AAV capsids, and they are deficient in essential properties for optimal gene therapy, such as targeted delivery, evasion of the immune system, higher levels of viral production, and greater transduction efficiency. Starting at Harvard in 2015, the authors set out to overcome the limitations of current capsids by developing new machine-guided technologies to rapidly and systematically engineer a suite of new, improved capsids for widespread therapeutic use.

Artificial Intelligence (AI) and Machine Learning are used to power a variety of important modern software technologies. AI also powers the facial recognition software commonly used by law enforcement, landlords, and private citizens. Of all the uses for AI-powered software, facial recognition is a big deal. Security teams from large buildings that rely on video surveillance – like schools and airports – can benefit greatly from this technology. An AI algorithm has the potential to detect a known criminal or an unauthorized person on the property.

Meili Gupta is about to ask another question. A poised and eloquent rising senior at elite boarding school Phillips Exeter Academy, Gupta, 17, is anything but the introverted, soft-spoken techie stereotype. She does, however, know as much about computer science as any high school student you'd ever meet. She even grew up faithfully reading the MIT Technology Review, the university's flagship publication, which shows, because Meili is the most ubiquitous student attendee at EmTech Next, a conference the publication held on campus this past summer on AI, Machine Learning, and "the future of work." Ostensibly, the conference is an opportunity for executives and tech professionals to rub elbows while determining how next-generation technologies will shape our jobs and economy in the coming decades. For me, the gathering feels more like an opportunity to have an existential crisis; I could even say a religious crisis, though I'm not just a confirmed atheist but a professional one as well.