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) …
Artificial Intelligence (AI), Machine Learning, Neural Networks … most of know these words. They're banded about as the'next big things' that promise to revolutionize the way you do business. This might well be true, but there are still many people that aren't aware of exactly what these technologies are, how they're already impacting our lives and how they have the potential to transform the way we do business. We know Siri and Alexa, the personal assistants by Apple (Siri) and Amazon (Alexa) to help us out in an increasing number of ways. Most of us know that these are AI-powered assistants, but few of us know about the thousands of algorithms, neural networks, random forests and gradient boosting that help make these assistants what they are and contribute to their growing sophistication and usefulness. Julia Medvid, Senior Client Partner at ITMAGINATION and Łukasz Dylewski, Head of Data Science, have extensive experience in introducing ITMAGINATION clients to AI and helping them to benefit from this game-changing technology.
Volvo has created a new business unit for its growing range of autonomous transport solutions. The new business area, Volvo Autonomous Solutions, will accelerate the development, commercialization and sales of autonomous transport solutions. Volvo says this will enable the company to meet "a growing demand" and to offer "the best possible solutions" to customers in such segments as mining, ports and transport between logistics centers, as a complement to today's products and services. With global developments that are characterized by higher demand for transportation, increasingly congested roads and major environmental challenges, the industry needs to provide transport solutions that are safer, have a lower environmental impact and are more efficient. Autonomous transport solutions, based on self-driving and connectivity technologies are well-suited for applications where there is a need to move large volumes of goods and material on pre-defined routes, in repetitive flows.
Data science has traditionally been an analysis-only endeavor: using historical statistics, user interaction trends, or AI machine learning to predict the impact of deterministically coded software changes. For instance, "how do we think this change to the onboarding workflow will shift user behavior?" This is data science (DS) as an offline toolkit to make smarter decisions. Increasing, though, companies are building statistical or AI/Machine Learning features directly into their products. This can make our applications less deterministic – we may not know exactly how applications behave over time, or in specific situations – and harder to explain.
Vehicle manufacturers know that they need to invent in autonomous technologies if they want to continue to remain relevant. As such, it should be no surprise that many car companies are investing in AI technologies to keep themselves competitive and relevant. Interviewed on an AI Today podcast episode, Jim Adler, Founding Managing Director of Toyota AI Ventures shared insights into the sort of investments Toyota AI Ventures is making in the industry, how the automotive industry is benefiting from these investments, and what non-automotive related AI and ML investments they are making. Founded in 2017, Toyota AI Ventures raised a $100 million fund to invest in artificial intelligence, cloud-based data, and robotics that may also leverage AI and cloud-based data. Toyota AI Ventures is a subsidiary of the Toyota Research Institute and helps AI ventures around the world to bring new artificial technology to the market.
"Innovation" is such an exciting concept, it's a shame the mainstream conversation about it has gotten so boring. My Twitter feed is an endless scroll of promises about the next-best, game-changing technology that's going to be "über of" whatever industry. The buzzwords alone are enough to make my eyes glaze over, which is a shame because the startups and founders emerging today, no longer beholden to the Silicon Valley zip code, have fresh approaches to solving the world's pressing problems. So with the global proliferation of thought-provoking solutions in fields like artificial intelligence, blockchain, sustainability, and diversity, how do we overcome innovation fatigue and remember why we love startups and their technology in the first place? Here's my take: innovation is only as exciting as its application.
Artificial Intelligence and Machine Learning solutions offer large possibilities to optimize and automate processes, save costs and make less human error possible for many industries. Food and Beverage is not an exception, where it can be beneficially applied in restaurants, bar and cafe businesses as well as in food manufacturing. These two segments have common use cases where AI in the food industry can be applied, as well as different ones, which is linked to different problems that must be solved. Knowing what goods to manufacture in large amounts or what dishes are the best choice to include in your restaurant menu is the key to increase earnings. Often customers' and market demands are changing very fast and so it is even more important to be one step ahead to take measures in time.
This model was open sourced back in June 2019 as an implementation of the paper Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis. This service is being offered by Resemble.ai. With this product, one can clone any voice and create dynamic, iterable, and unique voice content. Users input a short voice sample and the model -- trained only during playback time -- can immediately deliver text-to-speech utterances in the style of the sampled voice. Bengaluru's Deepsync offers an Augmented Intelligence that learns the way you speak.
Intelligent robots, intelligent virtual assistants, intelligent cars intelligently driving themselves, intelligent search systems learning and already knowing our browsing habits, interests, knowing what we are going to do online and even in real life. Siri and Alexa, Tesla, Amazon and Google, artificially intelligent algorithms that are everywhere, able to do many things instead of us. In the future, AI is going to change everything. As for now, there are lots of discussions about 4 main AI trends that are prone to shape the AI mechanized future of mankind. Here they are: deep learning, facial recognition, cloud, privacy and policy.
Microsoft's Ignite event traditionally attracts more from the developer ranks, but the technologies on display are increasingly of relevance to CIOs developing cloud strategies today. At Ignite 2019 in Orlando last week, Microsoft unveiled a new approach to analytics and data warehousing, Azure Synapse Analytics, and a new way to run Azure data services in anyone's cloud, Azure Arc. Get the latest cloud computing insights by signing up for our newsletter. With Azure Synapse Analytics Microsoft takes its Azure SQL Data Warehouse and turns up the volume to handle petabytes of data in its cloud. Some of the features -- such as dynamic data masking and column- and row-level security to provide granular access control -- are already generally available, while others -- notably integrations with Apache Spark, Power BI and Azure Machine Learning -- are still in preview.
With the adoption of the Agile and DevOps culture, where concepts supporting continuous delivery and continuous integration are prioritized, the entire domain of software development has gone through a massive transformation. Software development has now evolved more than ever before, both in the pace of development as well as delivery. With this evolution, another significant transformation in the industry of software development and quality assurance has been noticed. That includes the introduction of AI into the arena of test automation. While test automation is an absolute essential procedure to achieve the objectives of quality assurance and software testing, Artificial intelligence further assists in the CI/CD approach by empowering the test automation process and assisting in overcoming bottlenecks easily.