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) …
Significant advances have been made during the past few years in the ability of artificial intelligence (AI) systems to recognize and analyze human emotion and sentiment, owing in large part to accelerated access to data (primarily social media feeds and digital video), cheaper compute power, and evolving deep learning capabilities combined with natural language processing (NLP) and computer vision. According to a new report from Tractica, these trends are beginning to drive growth in the market for sentiment and emotion analysis software. Tractica forecasts that worldwide revenue from sentiment and emotion analysis software will increase from $123 million in 2017 to $3.8 billion by 2025. The market intelligence firm anticipates that this growth will be driven by several key industries including retail, advertising, business services, healthcare, and gaming. According to Tractica's analysis, the top use case categories for sentiment and emotion analysis will be as follows: "A better understanding of human emotion will help AI technology create more empathetic customer and healthcare experiences, drive our cars, enhance teaching methods, and figure out ways to build better products that meet our needs," says principal analyst Mark Beccue.
Tesla's second-quarter earnings call included a discussion of the computational hardware system that Tesla uses for its Autopilot driver assistance functionality. Tesla CEO Elon Musk revealed that Tesla is building its own computational hardware, as opposed to the traditional automotive approach of sourcing computational units from semiconductor suppliers. Furthermore, Musk revealed that Tesla's computer is, "an order of magnitude improvement in the frames per second." Musk included the top three leaders of Autopilot on the call: Stuart Bowers (VP of Engineering), Peter Bannon (Director of Silicon Engineering), and Andrej Karpathy (Director of AI). But it's an incredible job by Pete and his team to create this, the world's most advanced computer designed specifically for autonomous operation.
In the broad sweep of AI's current worldly ambitions, machine learning healthcare applications seem to top the list for funding and press in the last three years. Since early 2013, IBM's Watson has been used in the medical field, and after winning an astounding series of games against with world's best living Go player, Google DeepMind's team decided to throw their weight behind the medical opportunities of their technologies as well. Many of the machine learning (ML) industry's hottest young startups are knuckling down significant portions of their efforts to healthcare, including Nervanasys(recently acquired by Intel), Ayasdi (raised $94MM as of 02/16), Sentient.ai With all the excitement in the investor and research communities, we at TechEmergence have found most machine learning executives have a hard time putting a finger on where machine learning is making its mark on healthcare today. We've written this article, not to be a complete catalogue of possible applications, but to highlight a number of current and future uses of machine learning in the medical field, with relevant links to external sources and related TechEmergence interviews.
Netradyne, a leader in Artificial Intelligence (AI) technology focusing on driver and commercial fleet safety, today announced that its Driveri platform has been selected as the winner of the "Best AI-based Solution for Transportation" award from AI Breakthrough, an independent organization that recognizes the top companies, technologies and products in the global Artificial Intelligence (AI) market today. "Netradyne's recognition by the Artificial Intelligence Awards as being the best AI-based solution for transportation reiterates our company's belief that we are driving forward the potential for AI in all aspects of the transportation space including commercial trucking and autonomous vehicles," said Sandeep Pandya, Netradyne President. "This organization recognizes cutting edge AI technology at the highest levels and to have the Driveri platform mentioned alongside so many other impactful companies such as Google, NVIDIA and IBM is a tremendous honor. We are elated by the recognition and will continue to look for innovative ways to showcase AI's unique and impactful capabilities within transportation." The mission of the AI Breakthrough Awards is to honor excellence and recognize the innovation, hard work and success in a range of AI and machine learning related categories, including AI platforms, Deep Learning, Smart Robotics, Business Intelligence, Natural Language Processing, industry specific AI applications and many more.
The IT industry is experiencing an important transformation as companies invest in new technologies to drive growth and innovation. This trend is strongly reflected in our industry as E&P companies deal with enormous amounts of legacy, and increasing volumes of new data along with the expense and complexity of software to analyze and interpret this information. Challenges faced include operational efficiency, increasingly short project cycle times, communicating with a regional or global workforce, data silos, legacy software and restricted resources. Due to the industry's dynamics and its need for flexibility and information security, the cloud is increasingly seen as a viable and practical solution for the oil & gas industry, particularly now that Cloud service providers are building security into their software development processes. Security of data in the Cloud is often better today than in company's own networks.
Wave Computing, a Silicon Valley AI startup specializing in data flow processing of Deep Neural Networks, has acquired MIPS Technologies for an undisclosed amount. Wave projects that the acquisition will be immediately cash-flow positive and accretive to its balance sheet and valuation. The deal logic is pretty sound, adding new markets such as edge AI computing while giving the company in-house RISC cores it can use for its next-generation DataFlow Processing Unit datacenter AI chip. Who is Wave Computing, and why does it need MIPS? Wave is an early innovator in AI silicon geared towards datacenter use, to train deep neural networks (DNNs) and run those networks for predictions and classifications.
The longevity and biotechnology industries are focusing on aging in a big way, and it's beginning to show. The fields of Artificial Intelligence (AI) and regenerative medicine are putting their money on combating aging and age-related diseases, and the benefits are likely to be immense. While biotechnology and AI are relatively new concepts, the announcements of funding and collaboration yesterday by and between three companies are bringing those concepts that much closer to the forefront of medicine. Insilico Medicine, a Baltimore-based next-generation AI company specializing in the application of deep learning for target identification, drug discovery and aging research, yesterday announced a collaboration agreement with WuXi AppTec, a leading global contract research outsourcing provider based in Shanghai, China, serving the pharmaceutical, biotech, and medical device industries. "It's a big step not only for Insilico Medicine but for AI and the pharmaceutical industries," said Alex Zhavoronkov, PhD, CEO of Insilico Medicine, Inc.
Zebra Medical Vision, a machine and deep learning start-up, has raised $30 million (€25.47 million) in C round funding, bringing the total investment in the company to $50 million (€42.45 million). The company is also unveiling its Textray chest X-Ray research, which it claims is the most comprehensive AI research conducted on chest X-Rays to date, providing a glimpse into a future automated chest X-Ray analysis product being developed by the company. This round of investment is led by aMoon Ventures with the participation of strategic healthcare investors Aurum, Johnson & Johnson Innovation JJDC Inc. and Intermountain Healthcare and leading global AI experts Fei Fei Lee and Richard Socher. These new investors are joining a list of top existing investors Khosla Ventures, NVIDIA, Marc Benioff, OurCrowd and Dolby Ventures who also participated in this C round. The chest X-Ray AI analytics product was trained using nearly 2 million images to identify 40 different common clinical findings.
Artificial intelligence (AI) technology is progressing at a rapid pace, as is the application of the technology to solve real-world problems. While the market for chipsets to address deep learning training and inference workloads is still a new one, the landscape is changing quickly – in the past year, more than 60 companies of all sizes have announced some sort of deep learning chipset or intellectual property (IP) design. A new report from Tractica finds that virtually every prominent name in the technology industry has acknowledged the need for hardware acceleration of AI algorithms and the semiconductor industry has responded by offering a wide variety of solutions. Tractica forecasts that the market for deep learning chipsets will increase from $1.6 billion in 2017 to $66.3 billion by 2025. System-on-a-chip (SoC) accelerators such as those found in mobile devices will lead the market in terms of sheer volumes by the end of the forecast period, followed by application-specific integrated circuits (ASICs) and graphics processing units (GPUs).
Black Knight announced Monday its acquisition of HeavyWater, a provider of artificial intelligence and machine learning to the financial services industry. Black Knight explained it plans on integrating HeavyWater's AIVA solution, which leverages artificial intelligence and machine learning to perform operational functions more efficiently than traditional methods, into its premier solutions. It will also make the technology available to its clients looking to utilize AI within other parts of their organizations. "With the cost of origination and servicing at, or near, all-time highs, AIVA is poised to help increase efficiencies for Black Knight clients," Black Knight CEO Anthony Jabbour said. "AI, machine learning and neural network solutions are the future of delivering enhanced productivity and capabilities to our clients, and we are very excited about the potential HeavyWater has to offer."