If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
According to a new Gartner study, AI is the top priority for business leaders for the third year in a row. The AI market is now on its path to reaching $126 billion by 2025, with no signs of slowing down anytime soon. Hence it's critical for CEOs to grasp the reins and steer their companies into the digital age. Metaverse may be all the rage these days, fuelling popular imagination, taking over movies, games and other pop culture, but when it comes down to the brass tacks, the top bosses at organisations worldwide continue to swear by Artificial Intelligence (AI) to drive global growth. AI has become an inseparable part of an organisation.
As machine learning models become increasingly sophisticated, there is a growing concern that they may contain hidden biases that could lead to inaccurate or unfair predictions. In this blog post, we'll explore the issue of bias in natural language processing (NLP), and discuss some methods for detecting and mitigating it. Adoption of NLP has exploded in the last few years, and this growth is only expected to accelerate. According to Statista, in 2025 the NLP market will be nearly 14 times larger than it was in 2017. Much of this growth will be driven by adoption in the healthcare, retail and financial services industries--to name a few.
HealthCare Global Enterprises Ltd (HCG) on Monday announced that it has deployed Sigtuple's AI100 making HCG the first hospital chain to equip the Hematopathology labs across its network with AI-powered screening solutions for cancer detection and disease management. According to the company's press statement, SigTuple's AI100 is the premier solution for AI-assisted digital hematopathology. It is also the only digital hematopathology solution available that is economical and robust enough for wide-scale adoption, it claimed. "As manual microscopy is still the standard in diagnosing several critical disorders like cancers, infections, etc., in the absence of a pathologist at site in laboratories outside urban areas, these samples need to be shipped to central reference laboratories for review. Apart from the logistic challenges and associated delays in turnaround times, there is also limited expertise available for providing high quality diagnostics at remote locations," it stated.
Ivanti worked with global digital transformation experts and surveyed 10,000 office workers, IT professionals, and the C-Suite to evaluate the level of prioritization and adoption of DEX in organizations and how it shapes the daily working experiences for employees. The report revealed that 49% of employees are frustrated by the tech and tools their organization provides and 64% believe that the way they interact with technology directly impacts morale. Conflicting views remain between C-Suite, IT, and employees when it comes to the future of work and technology's role in enabling the culture of hybrid work. Just 13% of knowledge workers prefer to work exclusively from the office, yet 56% of CXOs still feel that employees need to be in the office to be productive, although 74% of the C-Suite report they are more productive since the start of the pandemic – showing a disconnect between what they have experienced and what they believe employees need to do to be productive. Globally the C-Suite's number one priority was employee productivity, with workplace culture and employee satisfaction falling further down the list.
In 1869, the English judge Baron Bramwell rejected the idea that "because the world gets wiser as it gets older, therefore it was foolish before." Financial regulators should adopt this same reasoning when reviewing financial institutions' efforts to make their lending practices fairer using advanced technology like artificial intelligence and machine learning. If regulators don't, they risk holding back progress by incentivizing financial institutions to stick with the status quo rather than actively look for ways to make lending more inclusive. The simple, but powerful, concept articulated by Bramwell underpins a central public policy pillar: You can't use evidence that someone improved something against them to prove wrongdoing. In law this is called the doctrine of "subsequent remedial measures." It incentivizes people to continually improve products, experiences and outcomes without fear that their efforts will be used against them.
The opening of Graphcore's Japan office is another hugely significant milestone in the company's rapid growth across Asia. Few nations are as closely associated with the development and adoption of leading-edge technology, so it is a privilege to be supporting Japan's continued innovation in artificial intelligence. To launch our business here, with two of the country's most trusted technology resellers, SCSK and HPC Systems, reflects the maturity of our business and our deep commitment to Graphcore customers. It is my personal privilege to be leading our operation in Japan. After a career that has taken me to some of the world's leading computer companies, including Cray, HPE, Compaq and DEC, I see in Graphcore the same potential to define a technology that will change our world.
Artificial intelligence (AI) is rapidly evolving and becoming ubiquitous across virtually every industry. AI solutions allow organizations to achieve operational efficiencies, gain insights into customer behavior, measure key performance indicators (KPIs), and leverage the power of big data, among other things. Similarly, the electric vehicles (EV) market has gained traction in recent years. It's more common to see drivers cruising in EVs, whether a Tesla, Chevy Bolt, or Nissan Leaf. EVs are becoming popular among eco-conscious consumers because they offer more eco-friendly benefits than traditional gas-powered vehicles.
But if you ask the co-founders of Modular, a startup emerging from stealth today, the software used to develop it is "monolithic," fractured into silos piled with layers of complexity. Big Tech companies have made helpful contributions, like TensorFlow and PyTorch -- AI development frameworks maintained by Google and Facebook, respectively. Modular aims to change that. Founded by former Apple and Google engineers and execs, the company today closed a large ($30 million) seed round led by GV (formerly Google Ventures), with participation from Greylock, The Factory and SV Angel to realize its vision of a streamlined, platform-agnostic AI system development platform. "The industry is struggling to maintain and scale fragmented, custom toolchains that differ across research and production, training and deployment, server and edge," Modular CEO Chris Lattner told TechCrunch in an email interview.
Who is responsible when AI harms someone? A California jury may soon have to decide. In December 2019, a person driving a Tesla with an artificial intelligence driving system killed two people in Gardena in an accident. The Tesla driver faces several years in prison. In light of this and other incidents, both the National Highway Transportation Safety Administration (NHTSA) and National Transportation Safety Board are investigating Tesla crashes, and NHTSA has recently broadened its probe to explore how drivers interact with Tesla systems.
Nearly 87 per cent of enterprises in India are likely to increase annual artificial intelligence (AI) spending by more than 10 per cent in the next three years, a new report showed on Tuesday. Approximately 80 per cent of enterprises in the country have at least one AI model in production, indicating an extensive penetration of AI/machine learning (ML) across enterprises. Within providers, too, 64 per cent have AI/ML as a core element for many of their products, as against 56 per cent of their global counterparts, according to the report by Bain & Company's, in collaboration with Microsoft and the Internet and Mobile Association of India (IAMAI). "While the availability of data and cloud-based infrastructure have aided AI adoption, concerns related to data security, infrastructure, and management continue to be the most significant barriers for enterprises," said Velu Sinha, Partner, Bain & Company and co-author of the report. The report was launched by Amitabh Kant, CEO, NITI Aayog, in the presence of top executives from the companies.