The metaverse is a shared virtual 3D world or worlds, which are interactive and collaborative. It encompasses a range of technologies in the field of collaborative spatial computing. The technologies include interactive 3D graphics, augmented reality ("AR"), virtual reality ("VR"), online economies, multi-user gaming and more. Once viewed as science fiction, the metaverse is now viewed as the future of gaming, entertainment, brands, e-commerce and enterprises. Any device capable of rendering an immersive 3-dimensional experience (including a PC or even an iPhone) is considered to be metaverse capable.

Companies in the Semiconductor – General industry are at the forefront of the ongoing technological revolution based on HPC, AI, automated driving, IoT and so on. These semiconductors also enable the cloud to function and help analyze the data into actionable insights that can be used by companies to operate more efficiently. If anything, the pandemic has strengthened the conviction that these technological changes are required and inevitable, because it is these technology platforms that enabled us to function when it was unsafe for us to go to work or meet people. Even with the opening up of the economy, the race to digitization, cloud, AI, etc. is expected to continue at an accelerated rate, driving strong demand for semiconductors. NVIDIA has pioneered and built a whole lot of this cutting-edge technology, so it remains a top recommendation.

Machine learning ("ML") has been gaining precedence over the past few years as organizations are rapidly implementing ML solutions to increase efficiency by delivering more accurate results as well as providing a better customer experience. Notably, when it comes to automation, ML has become a driving force as it involves training the Artificial Intelligence ("AI") to learn a task and carry it out efficiently, minimizing the need for human intervention. In any case, ML was already witnessing rapid adoption and the outbreak of the COVID-19 pandemic last year helped in accelerating that demand, as organizations began to rely heavily on automation to carry out their operations. Markedly, ML is gradually becoming an integral part across various sectors as the trend of digitization is picking up. Notably, ML is finding application in the finance sector as among other usages, it helps in better fraud detection and enabling automated trading for investors.

The COVID-19 pandemic has given employers ample reasons to look for ways to substitute man with machine. The shift in trend toward automation has accelerated in the past year. Businesses were suffering huge losses due to the lockdowns, leading to decline in productivity. Artificial intelligence (AI) tools that were perceived to give a competitive edge or a'nice-to-have' technology prior to 2020 became essential for several companies across the globe to stay afloat. All the more, AI has been deployed by several organizations during the pandemic to provide information to the public, when physical interactions were a complete no-no.

The COVID-19 pandemic has given employers ample reasons to look for ways to substitute man with machine. The shift in trend toward automation has accelerated in the past year. Businesses were suffering huge losses due to the lockdowns, leading to decline in productivity. Artificial intelligence (AI) tools that were perceived to give a competitive edge or a'nice-to-have' technology prior to 2020 became essential for several companies across the globe to stay afloat. All the more, AI has been deployed by several organizations during the pandemic to provide information to the public, when physical interactions were a complete no-no.

The implementation of artificial intelligence and machine learning in the healthcare sector has been rather diverse and extensive over the past few months, owing to the coronavirus pandemic. The reliance on these technologies is growing, primarily because of their ability to simplify the assessment of complicated data and cases. Therefore, now would be the ideal time for one to look at a couple of AI stocks from an investment perspective. Looking closely at the growth prospects of AI in the healthcare sector, one finds can find many. According to a report by Markets and Markets, artificial intelligence in the global healthcare market is expected to grow from $4.9 billion in 2020 to $45.2 billion by 2026 at a CAGR of 44.9%. While the major reasons for using artificial intelligence in healthcare are the rising volume of healthcare data and increasing complexities of datasets, the need to bring healthcare costs down, and improving computing power and lessening hardware costs.

Adesto Technologies Corporation IOTS fourth-quarter 2019 results are expected to benefit from strong demand for the company's IOT related offerings. For the quarter, the company expects revenues in the range of $32-$35 million. The Zacks Consensus Estimate for revenues is currently pegged at $33.6 million, indicating growth of 19.5% from the year-ago quarter. The consensus mark for fourth-quarter earnings has been steady at 4 cents over the past 30 days. The company had reported loss of 4 cents in the year-ago reported quarter.

Machine learning (ML) is hailed as one of the most impactful technologies in the AI spectrum. Comprising algorithms, ML applications are capable of enabling devices to learn, improve and make decisions automatically, without any explicit programming or human involvement. The application of ML has grown rapidly over the past years, bringing out the power of data in a whole new way. Devices operating on voice commands, recommendations from online search engines, real-time advertisements on web pages, image recognition and cyber fraud detection are some of the most common instances of ML. The technology has proven itself to be ground-breaking for the transportation industry by making self-driving cars a reality.

Machine learning (ML) is hailed as one of the most impactful technologies in the AI spectrum. Comprising algorithms, ML applications are capable of enabling devices to learn, improve and make decisions automatically, without any explicit programming or human involvement. The application of ML has grown rapidly over the past years, bringing out the power of data in a whole new way. Devices operating on voice commands, recommendations from online search engines, real-time advertisements on web pages, image recognition and cyber fraud detection are some of the most common instances of ML. The technology has proven itself to be ground-breaking for the transportation industry by making self-driving cars a reality.

Artificial intelligence (AI) has taken the world by storm. Burly robots and humanoids are common in sci-fi but it would not be too ambitious to say that the human race may see a cyborg infiltration down the line. With the emergence of AI, various sectors such as defense, medical and aerospace are increasingly making use of the technology to boost productivity and cost-effectiveness. This is why investing in AI-related stocks is a prudent decision at this point. An area which is already experiencing a massive usage of machine learning and robotics is the defense sector. Drew Cukor, chief of the U.S. Department of Defense's (DoD) Algorithmic Warfare Cross-Function Team stated on Mar 6, 2018 that the near future is about to observe humans and computers working "symbiotically" in order to increase the efficacy of a weapon system to be able to detect a target and obliterate it.