An artificial intelligence system is capable of being an "inventor" under Australian patent law, the federal court has ruled, in a decision that could have wider intellectual property implications. University of Surrey professor Ryan Abbott has launched more than a dozen patent applications across the globe, including in the UK, US, New Zealand and Australia, on behalf of US-based Dr Stephen Thaler. They seek to have Thaler's artificial intelligence device known as Dabus (a device for the autonomous bootstrapping of unified sentience) listed as the inventor. The applications claimed Dabus, which is made up of artificial neural networks, invented an emergency warning light and a type of food container, among other inventions. Several countries, including Australia, had rejected the applications, stating a human must be named the inventor.

Blockchain and AI make a formidable alliance, especially when it comes to security and data management. So in order to protect people's data with blockchain and AI tech for good, we have to build and deploy an ecosystem with an open source set of APIs that limits how much technology makers can learn about individual customers. Artificial Intelligence solutions are already being deployed within all our interactions on social media and the internet, from the sensors on our IoT driven smartphones to our financial, wellness and healthcare data. Adapting future AI, it is now being integrated on the top of blockchains solutions too, especially in the financial industry and supply chain transactions. This will be increasingly intertwined with Machine Learning solutions, capability and even opening up new ways of creating new social media, wellness, and financial products.

Airplanes and automobiles, databases and personal computers – all entities with ubiquitous form factors today, but that started out with diverging architectures. So it's not surprising that the shape of edge AI chip technology is similarly diversified. These are nascent days for AI chips. And with numerous designs in the market, there's unlikely to be a common architecture anytime soon. Today, established vendors and startup chip houses alike have jumped into the fray in a bid to complement or displace conventional microprocessors and controllers.

Pat Calhoun, a visionary leader focused on UX and adoption, is the CEO and Founder of Espressive, transforming enterprise self-help with AI. One of the most dramatic workplace shifts caused by the pandemic is the escalation of digital transformation initiatives. The numbers say it all. According to research by Twilio, 79% of digital transformation budgets grew in response to the pandemic -- and 26% grew "dramatically." Gartner, Inc. also found that over 80% of CEOs have a digital transformation program underway, and 69% are using Covid-19 as a catalyst to focus on resigning their businesses.

We can easy to set up a training environment from a notebook with "click" for elastic of CPUs/GPUs * Connectivity and easy to deploy – AWS SageMaker is AWS managed service and it easy to integrate with other AWS services inside of a private network. Which also impact to big data solution, ETL processed with data can be processing inside of a private network and reduce cost for the transfer. AWS managed service will help to reduce the resource we need to create.

"If you talk about the India story, every year there are around 450,000 road crashes, in which 150,000 people die. Accidents impose significant cost as much as 3% of GDP every year," says Selva Ramanujam, CEO of Montbleu Technologies. "What we want to achieve is to build a culture of safe driving behavior, encouraging drivers to drive with caution and at an appropriate speed for the conditions. Using this software, we will capture the data of the driver taking a risk at each moment and publish a driving behavior score. For those with a lower score, we coach them with continuous feedback, that gives the driver an opportunity to change driving behavior in order to influence the cost of vehicle insurance cover.

With digital marketing, good, clean, and insightful data is a key pillar which a business stands to drive growth and profits. Having clear and precise data-driven outcomes should be a priority for all marketers. When used in tandem with well-defined marketing and sales goals, and various marketing tools and techniques, companies will discover that their lead to sale conversion process can be far less cumbersome and more rewarding. Possessing clean data will help marketers identify detailed segments based on user attributes, past behaviours, interactions, and other necessary data points. Data can be leveraged for highly targeted campaigns which will drive marketing return on investment (ROI).

But Beijing has become alarmed at the growing power of Big Tech -- including the risk that personal information of senior officials could leak overseas -- and has moved this year to rein in China's Internet giants. This included derailing the IPO plans of mobile payment titan Ant Group, launching a probe into Didi Chuxing, the Chinese equivalent of Uber, and a ban on the country's lucrative online, for-profit tutoring services for students.

All the sessions from Transform 2021 are available on-demand now. The pandemic spurred investments in AI across nearly every industry. That's according to CB Insights' AI in the Numbers Q2 2021 report, which found that AI startups attracted record funding -- more than $20 billion -- despite a drop in deal volume. While the adoption rate varies between businesses, a majority of them -- 95% in a recent S&P Global report -- consider AI to be important in their digital transformation efforts. Organizations were expected to invest more than $50 billion in AI systems globally in 2020, according to IDC, up from $37.5 billion in 2019. And by 2024, investment is expected to reach $110 billion.

All the sessions from Transform 2021 are available on-demand now. Ethics and artificial intelligence have become increasingly intertwined due to the pervasiveness of AI. But researchers, creators, corporations, and governments still face major challenges if they hope to address some of the more pressing concerns around AI's impact on society. Much of this comes down to foresight -- being able to adequately predict what problems a new AI product, feature, or technology could create down the line, rather than focusing purely on short-term benefits. "If you do believe in foresight, then it should become part of what you do before you make the product," AI researcher and former Googler Margaret Mitchell said during a fireside chat at VentureBeat's Transform 2021 event today.