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) …
The 1.5 meter, silvery gray velociraptor lunges forward, interrupting the flight of the tennis ball with its head before the ball can get to the soccer net at the end of the gym. Its tail stretches out, stopping another ball. It pivots, somewhat clumsily, and runs three steps in the other direction to intercept a third ball. Robots building Teslas aren't as sophisticated as AI velociraptors that tend goals It's been doing this for an hour, running back and forth as a trio of tennis ball machines toss yellow balls in various loopy ways toward the net. It's a game that its creators have invented to rapidly improve its coordination. But then it stops trying to intercept the balls, although it still twitches toward them.
The Machine Learning Summit is designed for everyone from data scientist to business professionals. If you've ever been curious about artificial intelligence and machine learning, whether you're just getting started on your machine learning journey or already a machine learning practitioner, this Summit will provide you with knowledge of what's on the horizon for machine learning. To attend the Machine Learning Summit, purchase a ticket to AWS re:Invent 2019. Once reserved seating opens in the fall, you will be able to register for a seat.
This year, we saw a dazzling application of machine learning. The OpenAI GPT-2 exhibited impressive ability of writing coherent and passionate essays that exceed what we anticipated current language models are able to produce. The GPT-2 wasn't a particularly novel architecture – it's architecture is very similar to the decoder-only transformer. The GPT2 was, however, a very large, transformer-based language model trained on a massive dataset. In this post, we'll look at the architecture that enabled the model to produce its results. We will go into the depths of its self-attention layer. My goal here is to also supplement my earlier post, The Illustrated Transformer, with more visuals explaining the inner-workings of transformers, and how they've evolved since the original paper. My hope is that this visual language will hopefully make it easier to explain later Transformer-based models as their inner-workings continue to evolve.
H2O is a fully open-source, distributed in-memory machine learning platform with linear scalability. H2O supports the most widely used statistical & machine learning algorithms, including gradient boosted machines, generalized linear models, deep learning, and many more. H2O also has an industry-leading AutoML functionality (available in H2O 3.14) that automates the process of building a large number of models, to find the "best" model without any prior knowledge or effort by the Data Scientist. H2O AutoML can be used for automating the machine learning workflow, which includes automatic training and tuning of many models within a user-specified time-limit. Some of the important features of H2O's AutoML are: H2O's AutoML can also be a helpful tool for the novice as well as advanced users.
Debate about the role of automation in the workplace has raged for years. The first major study on the subject was conducted in 2013 and it suggested that artificial intelligence and robots could threaten 50% of jobs in the U.S. A few years later in 2018, the OECD released a more detailed report suggesting that just 14% of jobs in OECD countries were "highly automatable". Earlier this year, the Office for National Statistics analysis suggested that this figure was now as low as 7%. Slowly but surely, the fear about automation at work has subsided. In fact, our global research of more than 34,000 people across 18 countries, released this month, has found that workers don't fear technology or automation--69% of them believe it will actually enhance, not replace, their jobs.
LOS ANGELES, CA, Oct. 20, 2019 (GLOBE NEWSWIRE) -- via NEWMEDIAWIRE – iPR Software, the leader in Online Newsrooms, Digital Publishing, Digital Asset Management (DAM) solutions, and customized integrated solutions, announced its largest technology rollout to date at Public Relations Society of America's International Conference in San Diego, California. With the launch of "Metatron," iPR Software's new application empowers Artificial Intelligence (AI) cloud capabilities as well as integrating the power of machine learning into DAM and customized software platforms to increase productivity and corporate asset sharing across multiple customer ecosystems. This latest software release further advances the company's vision for clients to publish their news and information to Traditional and Social media channels and better engage their B2B & B2C audiences while increasing traffic to their branded media and corporate assets. Leading organization's today are utilizing cloud applications to access the latest technology with encryption algorithms they can securely manage, publish, and share rich branded media content. Metatron introduces core, cloud-based software features that enable customers to securely publish and share key digital media and corporate assets, target practical enterprise use cases, increase workflow efficiencies, and automate mundane tasks to reduce data and storage errors.
Artificial intelligence (AI) expert and Flamingo Ai Founder and Executive Director Dr Catriona Wallace is set to share her insights on what we can look forward to in a world with more advanced AI, at this year's CEBIT expo. The keynote, titled'AI: Human Machine: Who gets the upper hand?' will explore developments in AI, how it's being used and how it will transform the business world and life as we know it. "AI, described as the most powerful force equal in impact to the discovery of fire and the invention of electricity, will increasingly become the primary power driving the massive changes that [climate change and disruptive technologies] will bring," Wallace said. "With AI set to replace 40% of jobs and 30% of business interactions in the next five years, and the time of'singularity', where machines may become'smarter' than humans possibly just 20 years away, the onus will be on people to successfully navigate the Fourth Industrial Revolution." NSW Minister for Jobs and Investment Stuart Ayres said CEBIT Australia will provide an international forum for technology companies to do business and discuss the future, including the impact of AI and how it can be harnessed to secure new jobs.
Perkovic's Introduction to Programming Using Python is more than just an introduction to programming. It is an inclusive introduction to Computer Science that takes the pedagogical approach of "the right tool for the job at the right moment," and focuses on application development. The book's approach is hands-on and problem-oriented, with practice problems and solutions appearing throughout the text. The text is imperative-first, but does not shy away from discussing objects early where appropriate. Discussions of user-defined classes and Object-Oriented Programming appear later in the text, when students have more background and the concepts can be motivated.
This chapter presents probability logic as a rationality framework for human reasoning under uncertainty. Selected formal-normative aspects of probability logic are discussed in the light of experimental evidence. Specifically, probability logic is characterized as a generalization of bivalent truth-functional propositional logic (short "logic"), as being connexive, and as being nonmonotonic. The chapter discusses selected argument forms and associated uncertainty propagation rules. Throughout the chapter, the descriptive validity of probability logic is compared to logic, which was used as the gold standard of reference for assessing the rationality of human reasoning in the 20th century.
Our research aims to develop interactive, social agents that can coach people to learn new tasks, skills, and habits. In this paper, we focus on coaching sedentary, overweight individuals (i.e., trainees) to exercise regularly. We employ adaptive goal setting in which the intelligent health coach generates, tracks, and revises personalized exercise goals for a trainee. The goals become incrementally more difficult as the trainee progresses through the training program. Our approach is model-based - the coach maintains a parameterized model of the trainee's aerobic capability that drives its expectation of the trainee's performance.