BrainChip Holdings Ltd (ASX: BRN), (OTCQX: BRCHF), a leading provider of ultra-low power high performance artificial intelligence technology and the world's first commercial producer of neuromorphic AI chips and IP, today announced that the next episode of its "This is our Mission" podcast will air early next year rather than its traditionally scheduled timeslot in December, to give guests and listeners time to enjoy the holidays and year-end celebrations. The series will go back to its regular monthly releases upon its return. Launched in 2020, the BrainChip Podcast is a monthly event intended to provide company and industry insight for the engineering community in target markets, as well as analysts, technical and financial press and investors. Guests have included company executives explaining BrainChip's technology and advances made towards marketability, as well as leading industry and academic experts who have provided insight into the broader market and BrainChip's place within it as part of "Outside Looking In" conversations. "This has been an incredible year interviewing incredible people to help listeners, investors and even those within the company learn about this incredible emerging marketplace and gain insight into aspects of AI from different perspectives," said Rob Telson, Vice President of Worldwide Sales at BrainChip and frequent podcast host.

Abacus.AI, announced today that it has been recognized as a Cool Vendor based on the October 11, 2021 Gartner Report "Cool Vendors in AI Core Technologies" by Farhan Choudhary, Alexander Linden, Pieter den Hamer, Arun Chandrasekaran, and Jim Hare. Abacus.AI is the world's first end to end AI and ML platform and has custom vertical specific for many enterprise AI use-cases including personalization, forecasting, NLP and vision. The platform may be used by data science teams who want to plug and play their own models and instantly deploy their models to production or by line of business owners who may want to use Abacus's innovative neural-architecture-search techniques to build a custom model based on the shape of their datasets and the use-case. Its AI platform democratizes the use of AI enabling organizations of all sizes to design, train, and operationalize machine and deep learning models. In addition, Abacus.AI has vertically integrated support for several common enterprise use-cases. This allows organizations of all sizes, from small startups to Fortune 500 companies, to use the company's state-of-the-art platform to enhance their AI adoption.

IRVINE, Calif., Dec. 16, 2021 (GLOBE NEWSWIRE) -- Seoul Robotics, the 3D perception solution company using deep learning AI to power the future of mobility, today announced that in 2021 the company more than doubled the number of partnerships and global employees. In July alone, Seoul Robotics closed more business than in the entirety of 2020. Since launching in North America in January 2021, Seoul Robotics has introduced three plug-and-play 3D perception systems, Discovery, Voyage, and Endeavor, as well as the most advanced version of its 3D perception platform, SENSR 2.2. SENSR 2.2 is the only 3D perception software on the market leveraging deep learning AI and is compatible with over 75 different makes and models of 3D sensors, including LiDAR. Over the past year, Seoul Robotics has secured and scaled solutions with several top-tier companies and government entities, including multiple Tier-1 original equipment manufacturers (OEMs) and Departments of Transportation.

A Korean research team developed a technology for detecting humans lying on the road in real-time. Therefore, preventing safety accidents in the city and rapidly responding to it will be possible, and a safer society is expected to be accomplished. The Electronics and Telecommunications Research Institute (ETRI) announced that it applied the technology of Visual AI ‘DeepView’ to Daejeon Metropolitan City in earnest to prevent safety accidents in the city and promptly respond to them. DeepView is an AI technology recognizing human behavior. It detects people lying on the road through surveillance cameras in real-time. As it can be applied to preventing safety accidents caused by drinking, fainting, etc. and performing prompt emergency rescue measures. It is expected to become the core technology for making a safe city.

Yaochu Jin is doing research on nature-inspired intelligent technological systems that organize themselves in a changing environment. How can artificial intelligence (AI) draw on principles from nature to solve complex problems? When it comes to recognizing patterns in large amounts of data, AI is faster and more capable than humans. However, it has difficulties when it has to make connections or deal with uncertainties and fuzziness. Through evolution, development, and learning, nature has developed much more practical problem-solving solutions. Yaochu Jin, the Alexander von Humboldt Professor of Artificial Intelligence at Bielefeld University since the autumn, is looking at how such principles can be transferred to AI.

WASHINGTON – The National Geospatial-Intelligence Agency has selected a team of commercial and academic partners to build an artificial intelligence system with synthetic data, which will further help the agency determine how it builds machine learning algorithms moving forward. Orbital Insight was issued a Phase II Small Business Innovation Research contract by the NGA, the company announced. It will collaborate with Rendered.ai As the organization charged with analyzing satellite imagery for the intelligence community, NGA has put increased emphasis on using AI for its mission. The agency sees human-machine pairing as critical for its success, with machine learning algorithms taking over the rote task of processing the torrent of satellite data to find potential intelligence and freeing up human operators to do more high level analysis and tasks.

Virtus AllianzGI Artificial Intelligence & Technology Opportunities Fund (NYSE: AIO), a diversified closed-end fund, today announced that it will institute a managed distribution plan effective with the distribution payable February 1, 2022. Coincident with the adoption of the plan, the Fund will raise its monthly distribution to $0.15 per share, a 20% increase from the distribution of $0.125 per share payable January 3, 2022. The increased distribution represents an annualized distribution rate of 6.7% based on the closing market price of $26.88 on December 16, 2021. The Fund is undertaking these actions as part of its ongoing efforts to enhance shareholder value by both seeking to provide a more attractive distribution rate and furthering its efforts to reduce the current discount to net asset value at which its shares currently trade. The Board also approved a change in the Fund's fiscal year end from February 28 to January 31, effective January 31, 2022.

The use of statistical methods to estimate or predict the behavior of a phenomenon in the future has been common practice in many disciplines such as health care, trading, auto insurance and customer relationship management. The goal of these methods is not necessarily the prediction of the exact outcome, but a determination of the likelihood of different outcomes, since in that case one can prepare accordingly. Machine learning has further empowered such methods, allowing them to become even more accurate by using more data and additional computation. Predictive models require lots of data, which can be problematic since storing such data is expensive and transferring such data can create a significant load on networks. What if there was a method that would allow for the training of predictive models without the need to transfer needed data in its original raw form.

LONDON--(BUSINESS WIRE)--Deep Knowledge Analytics, Big Innovation Centre and Innovation Eye launch'Artificial Intelligence in the UK: Industry landscape overview in 2021', the most comprehensive industry mapping made to date, profiling, categorising and analysing over 3,600 private and public sector entities across 20 sectors and 50 locations in the UK. The open-access report and IT platform, covers the latest developments in technology and innovation, best ranking companies and investors hubs, AI and COVID-19, policy and ethics, AI challenges and opportunities for the UK. Additionally, it profiles the top 100 UK AI experts and hubs, including think tanks, tech-hubs and doctoral training centres. The UK remains first in Europe and ranks third globally, behind the USA and China in developing AI technologies with a reported £9 billion investment growth for the industry between 2019 and 2021. The UK government continues to foster growth and industry development through initiatives in 5 key areas - human capital, lab to market developments, networking, regulation and infrastructure.

Utilidata, an industry leading grid-edge software company, announced today that it is developing a software-defined smart grid chip in collaboration with NVIDIA. The chip will be powered by NVIDIA's AI platform and embedded in smart meters to enhance grid resiliency, integrate distributed energy resources (DERs) -- including solar, storage, and electric vehicles (EVs) -- and accelerate the transition to a decarbonized grid. The U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) will be among the first to test the software-defined smart grid chip as a way to scale and commercialize the lab's Real-Time Optimal Power Flow (RT-OPF) technology, with support from the Solar Energy Technologies Office Technology Commercialization Fund. Originally developed with funding from DOE's Advanced Research Projects – Energy (ARPA-E) program, RT-OPF enables highly localized load control to seamlessly integrate an increasing number of DERs while ensuring stable and efficient grid operations. "To date, the scalability and commercial potential of technologies like RT-OPF have been limited by single-use hardware solutions," said Santosh Veda, Group Manager for Grid Automation and Controls at NREL. "By developing a smart grid chip that can be embedded in one of the most ubiquitous utility assets – the smart meter – this approach will potential enable wider adoption and commercialization of the technology and redefine the role of edge computing for DER integration and resiliency. Enhanced situational awareness and visibility from this approach will greatly benefit both the end customers and the utility."