Stenqvist dives into how Volvo is thinking about new technology, and we chat a bit about how it's approaching completely autonomous vehicles. Listen below or subscribe on your podcast app of choice. If you've got suggestions or topics you'd like covered on the show, be sure to email us or drop a note in the comments! And be sure to check out our other podcast, Engadget News!

It is undeniable that technological advances and cultural shifts have transformed our online universe over the years--especially with the recent surge in AI-generated content--but Deckelmann still isn't afraid of people on the internet. She believes they are its future. In the summer of 2022, when she stepped into the newly created role of CPTO, Deckelmann didn't know that a few months later, the race to build generative AI would accelerate to a breakneck pace. With the release of OpenAI's ChatGPT and other large language models, and the multibillion-dollar funding cycle that followed, 2023 became the year of the chatbot. And because these models require heaps of cheap (or, preferably, even free) content to function, Wikipedia's tens of millions of articles have become a rich source of fuel. To anyone who's spent time on the internet, it makes sense that bots and bot builders would look to Wikipedia to strengthen their own knowledge collections.

December is here, so you know what that means: holiday parties, new year's resolutions, and a slew of technology predictions. We decided to focus on a trend that matters most urgently to IT leaders--concrete artificial intelligence (AI) insights for your team and business. The potential impacts of AI are wide-ranging--as are the related forecasts, on everything from sentient to generative and responsible AI, to collaboration and automation. What will matter to IT leaders in 2023? We talked to AI and IT career experts to ask their opinions.

Brady, CEO of TheoremOne & Managing Partner at Halmos Ventures, is a serial entrepreneur & technologist on a mission to transform innovation. As C-suite executives continue to look at automated solutions to make work processes easier and more efficient, robotic process automation (RPA) is quickly becoming a strategy you can't ignore. Promising to reduce costs, streamline enterprise operations and free up workers to focus on higher value work, RPA looks to be a critical element of the future of enterprise technology. CIO defines it well: "RPA is an application of technology, governed by business logic and structured inputs, aimed at automating business processes. Using RPA tools, a company can configure software, or a'robot,' to capture and interpret applications for processing a transaction, manipulating data, triggering responses and communicating with other digital systems."

As the tech world inches a closer to the idea of artificial general intelligence, we're seeing another interesting theme emerging in the ongoing democratization of AI: a wave of startups building tech to make AI technologies more accessible overall by a wider range of users and organizations. Today, one of these, Baseten -- which is building tech to make it easier to incorporate machine learning into a business' operations, production and processes without a need for specialized engineering knowledge -- is announcing $20 million in funding and the official launch of its tools. These include a client API and a library of pre-trained models to deploy models built in TensorFlow, PyTorch or scikit-learn; the ability to build APIs to power your own applications; and the ability the create custom UIs for your applications based on drag-and-drop components. The company has been operating in a closed, private beta for about a year and has amassed an interesting group of customers so far, including both Stanford and the University of Sydney, Cockroach Labs and Patreon, among others, who use it to, for example, help organizations with automated abuse detection (through content moderation) and fraud prevention. The $20 million is being discussed publicly for the first time now to coincide with the commercial launch, and it's in two tranches, with equally notable names among those backers.

Did you miss a session at the Data Summit? This article was contributed by Atul Sharma, cofounder and CTO of Peak. The amount of data created, consumed and stored worldwide is set to increase by over 50% between now and 2025. Businesses understand that evaluating their data more effectively provides a competitive edge, and that it will be artificial intelligence, not business intelligence, that will unlock this potential -- but there's a striking gap between the scale of AI investment and tangible returns delivered. Fortune 500 companies are spending an average of $75 million on AI talent.

Research from STX Next, Europe's largest software development company specializing in the Python programming language, has found that 68% of chief technical officers (CTOs) have implemented machine learning at their company. This makes it overwhelmingly the most popular subset of AI, with others such as natural language processing (NLP), pattern recognition and deep learning also showing considerable growth. Despite the popularity of AI and its various subsets, it's also clear that AI implementation is still in its early phases and there's progress to be made in recruiting the talent needed for its development. In fact, 63% of CTOs reported that they aren't actively hiring AI talent and of those that are, over 50% report facing recruitment challenges. The findings were taken from STX Next's 2021 Global CTO Survey, which gathered insights from 500 global CTOs about their organization's tech stack and what they're looking to add to it in the future.

More than a quarter of a million developers, researchers, innovators, and creators are gearing up for the long-awaited #1 AI conference – NVIDIA GTC which is kick-starting on November 8, 2021. The four-day virtual event will highlight some of the latest advancements in AI, deep learning, data science, high-performance computing (HPC), robotics, data science, networking, graphics and more. The Keynote by Jensen Huang, NVIDIA Founder, President and CEO, named as one of the world's most influential people of 2021, is expected to inspire and showcase the latest developments in AI, new solutions and latest products that will help solve the world's toughest challenges. Don't miss this Keynote, which will be live on November 9, at 1:30 PM IST GTC will provide a great opportunity for developers to learn the advancements in the latest technologies from the world's top innovators, scientists, and researchers. In addition, startups, academia, and the largest enterprises will all come together at GTC, giving participants a unique opportunity to share ideas and collaborate on creating the future.

But the big data industry has significant inertia moving into 2021. In order to give our valued readers a pulse on important new trends leading into next year, we here at insideBIGDATA heard from all our friends across the vendor ecosystem to get their insights, reflections and predictions for what may be coming. We were very encouraged to hear such exciting perspectives. Even if only half actually come true, Big Data in the next year is destined to be quite an exciting ride. The "analytic divide" is going to get worse. Like the much-publicized "digital divide" we're also seeing the emergence of an "analytic divide." Many companies were driven to invest in analytics due to the pandemic, while others have been forced to cut anything they didn't view as critical to keep the lights on – and a proper investment in analytics was, for these organizations, analytics was on the chopping block. This means that the analytic divide will further widen in 2021, and this trend will continue for ...

I could spend the remainder of our time on this concept of job roles for artificial intelligence; it's a favorite topic for me. I am a big proponent of the discipline of data science being a team sport. We currently have our engineers and our analysts and our operators. And the roles and disciplines around data science and data engineers have been morphing out of an additional duty on analysts and engineers into its own sub sector, its own discipline. We're looking at a cadre of data professionals that serve almost as a logistics function to our operators who are doing the mission-level analysis.