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) …
A computer scientist who said she was pushed out of her job at Google in December 2020 has marked the one-year anniversary of her ouster with a new research institute aiming to support the creation of ethical artificial intelligence. Timnit Gebru, a known advocate for diversity in AI, announced the launch of the Distributed Artificial Intelligence Research Institute, or DAIR. Its website describes it as "a space for independent, community-rooted AI research free from Big Tech's pervasive influence." Part of how Gebru imagines creating such research is by moving away from the Silicon Valley ethos of "move fast and break things" -- which was Facebook's internal motto, coined by Mark Zuckerberg, until 2014 -- to instead take a more deliberate approach to creating new technologies that serve marginalized communities. That includes recognizing and mitigating technologies' potentials for harm from the beginning of their creation process, rather than after they've already caused damage to those communities, Gebru told NBC News.
At Databricks, we have had the opportunity to help thousands of organizations modernize their data architectures to be cloud-first and extract value from their data at scale with analytics and AI. Over the past few years, we've been fortunate to engage directly with customers across industries and regions about their data-driven aspirations – and the roadblocks that slow down their ability to get there. While challenges vary greatly among industries and even individual organizations, we have developed a rich understanding of the top four habits of data and AI-driven organizations. Before diving into the habits, let's take a quick look at how organizations have approached enabling data strategies. First, data teams have made technology decisions over time that propel a way of thinking that is based around technology stacks: data warehousing, data engineering, streaming real-time data science, and machine learning.
Don't miss our upcoming virtual workshop with John Snow Labs, Improve Drug Safety with NLP, to learn more about our joint NLP solution accelerator for adverse drug event detection. The World Health Organization defines pharmacovigilance as "the science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other medicine/vaccine-related problem." While all medicines and vaccines undergo rigorous testing for safety and efficacy in clinical trials, certain side effects may only emerge once these products are used by a larger and more diverse patient population, including people with other concurrent diseases. To support ongoing drug safety, biopharmaceutical manufacturers must report adverse drug events (ADEs) to regulatory agencies, such as the US Food and Drug Administration (FDA) in the United States and the European Medicines Agency (EMA) in the EU. Adverse drug reactions or events are medical problems that occur during treatment with a drug or therapy.
There is enormous interest in and momentum around using AI to reduce the need for human monitoring while improving enterprise security. Machine learning and other techniques are used for behavioral threat analytics, anomaly detection and reducing false-positive alerts. At the same time, private and nation-state cybercriminals are applying AI to the other side of the security coin. Artificial intelligence is used to find vulnerabilities, shape exploits and conduct targeted attacks. How does an enterprise protect the tools it is building and secure those it is running during the production process?
Whether you've used social media, a navigation app or a picture filter, chances are that Artificial Intelligence (AI) has impacted you. It's not just you — AI is impacting human rights worldwide, and this course will inform and educate you on how your rights are affected by AI, and how you can be empowered to guard these rights. UNESCO and UNITAR jointly launched a new, short online learning course on AI and Human Rights for youths aged 16 to 24. Experts break down complex concepts about AI into straight forward activities built around our daily technology interactions. The course focuses on how freedom of expression, right to privacy and the right to equality are impacted using AI.
The current attention trade shows, media outlets, and (more and more) vendors are devoting to quantum computing is far from transitory. This form of computing is almost certain to play an integral part in the most meaningful future developments of Artificial Intelligence--if not in those for today. The bifurcation of quantum computing's applicability to AI is clear. On the one hand, "Quantum computing is necessary to reach Artificial General Intelligence," denoted Kyndi CEO Ryan Welsh. On the other, quantum computing is able to solve a critical problem related to AI that is a vital steppingstone to actually achieving Artificial General Intelligence. According to Welsh, quantum computing methods have a definite capacity for "fusing the gap between continuous mathematics and discreet mathematics," which is at the crux of the dichotomy between statistical AI and symbolic AI for Natural Language Processing applications.
For the first-timers here, "A Thief's End" is the award-winning final act of Nathan Drake's story. I'll tip-toe around the plot details and just write that in the beginning of the game, which originally released in 2016, Drake is cajoled out of retirement to go on one last hunt for a long-dead pirate's treasure. "The Lost Legacy," which Naughty Dog released a year later, follows Chloe Fraizer and Nadine Ross -- two of the most compelling characters in the series -- on their own adventure through the Western Ghats, a mountain range on the southwest coast of India. Neither of these games is going to spoil whatever happens in Tom Holland's adventure as Nathan Drake. Sony has said that the movie "took inspiration from the games" but the story line is "completely unique."
Wendy Gonzalez is the CEO of Sama, the provider of accurate data for ambitious AI. Once associated with big New York City offices, patriarchal workplace culture and multi-million dollar budgets, the advertising industry has evolved considerably in the past century. Now diversified and modernized, remnants of the mid-century Madison Avenue advertising ecosystem are few and far between. But what's caused this shift? Industry leaders will be quick to tell you there's at least one tool that's been especially vital to this evolution: artificial intelligence (AI).
Artificial intelligence (AI) and machine learning (ML) are gaining acceptance quickly in the oil and gas industry. Between 2018 and 2020, the percentage of companies that had deployed these technologies more than doubled--from 13 to 32%. Today, 50% of oil and gas executives say they have already begun using AI to help solve challenges at their organizations and 92% are either currently investing in AI or plan to in the next 2 years. While these technologies have mostly been operationalized for specific use cases or particular processes, they are increasingly being incorporated into a whole host of systems and software to improve efficiency, productivity, and profitability. And the potential impact is significant: International Data Corporation estimates that the benefits enabled by AI and ML can reduce an organization's total costs by up to 20%, improve asset availability by 20%, and extend the lives of machines by years. Technologies Enable Transformation It's not AI and ML on their own that make a difference.
MotorDNA seeks to close the data gap between the Insurers, Consumers, Auto Lenders, Fleet Managers, Regulators, and OEMs with a platform to encourage the production and demand for safer vehicles. The US Automobile Insurance industry, valued at greater than $300B, is modernizing and transforming its products to mirror the transformation in the mobility space. Automobile technology is rapidly advancing, and vehicles are getting smarter. Safety features, sometimes referred to as ADAS (Advanced Driver Assistance Systems) and their effectiveness are progressing quickly on the journey to autonomous driving. However, vehicle build data is neither readily available in the market nor has it been organized to make it actionable for insurers to create products and pricing based on accurately assessing the risk of each vehicle.