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 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.

Juniper Networks, Inc. JNPR recently announced that its Wireless LAN platform from subsidiary -- Mist Systems -- has been selected by a leading Belgium-based transportation and logistics company, Transports Vervaeke. The latest collaboration is primarily aimed at leveraging Mist's AI-driven platform to enhance the productivity of the European company's workforce with modernized enterprise solutions. Markedly, the innovative network solution will be designed by Juniper's Elite Partner, Infradata, which provides cybersecurity and automation solutions to enterprises as well as network operators. Equipped with avant-garde cloud architecture, Mist is better known for leveraging its AI-driven network to enhance user experience. It also offers best-in-class subscription services like AI-supported virtual assistant Marvin, Asset Visibility, Wi-Fi Assurance and User Engagement for trouble shooting analytics as well as for seamless connectivity with key insight and automation.

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.

Broadcom AVGO recently launched Automation.ai, an AI-based software platform for supporting decision making processes across different industries. Large volumes of data often make digital transformation a challenging regime. This can lead to slower decision making. Automation.ai is a unique platform designed to ease complications stemming from the interference of diverse tools and data, and thereby facilitate informed decision making. Automation.ai correlates and examines data as well as powers Digital BizOps from Broadcom across different types of operations.

Ambarella AMBA recently announced a collaboration with Amazon's AMZN cloud computing arm, AWS, enabling customers to use Amazon SageMaker Neo cloud service to run ML models on devices based on Ambarella's CVflow-powered AI vision SoC (system on chip). Reportedly, this collaboration eliminates the need for developers to manually optimize ML models for devices based on Ambarella AI vision SoCs, preventing delays and errors in application development. The company will exhibit the collaboration with Amazon SageMaker Neo during CES 2020, to be held on Jan 7-10. Ambarella also named IP surveillance solution provider, VIVOTEK, as the first joint customer to leverage the single-click ML solution for edge applications. The company's CVflow suit of SoCs runs on an advanced 10-nanometer process, which enables the development of compact, high-performance vision systems with ultra-low-power operation.

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.

Cognex CGNX recently announced the acquisition of Seoul-based SUALAB, a developer of deep learning-based vision software. Although the financial terms of the acquisition have been kept under wraps, per a Pulse article the transaction price is estimated to be $168.6 million. Deep learning allows Cognex to solve the most complex vision application operations in factories faster, easier and in a cost-effective manner. The addition of SUALAB's Intellectual property and highly skillful engineering team, which specializes in deep learning, is expected to strengthen the company's product portfolio. The latest acquisition will help Cognex to reap benefits from strong prospects of the global deep learning system software market.