Originally published on Towards AI the World's Leading AI and Technology News and Media Company. If you are building an AI-related product or service, we invite you to consider becoming an AI sponsor. At Towards AI, we help scale AI and technology startups. Let us help you unleash your technology to the masses. It uses GPT-3, a language model with 175 billion parameters, making it one of the largest in existence.

Fears surrounding AI and cybersecurity reflect very real risks. AI-powered malware isn't a threat we need to worry about right now, but attackers have become adept at manipulating AI systems to their own advantage, essentially turning them against users. Widespread manipulation of the algorithms used on social media is already causing problems in many parts of the world. And as sophisticated AI tools become freely available, it would be naive not to expect adversaries to take advantage of the technology. But for now, we suspect that threat actors are using AI in rather indirect ways, such as for data analysis or by using tools to produce fake content.

The world's largest AI research conference is underway in Vancouver, Canada. Researchers are presenting more than 1,400 papers at the Neural Information Processing Systems (NeurIPS) conference, ranging from work that organizers believe has had the greatest impact over the past decade to Yoshua Bengio's continued march toward consciousness for deep learning. But even as the conference showed theoretical research and neuroscience-related papers on the rise alongside categories like algorithms and deep learning, the mushrooming of the event itself -- and the associated growing pains -- was a constant theme, and it speaks to the growth of the AI field in general. Organizers said that at the start of the conference Sunday, they expected about 400 people to show up for registration. All told, NeurIPS 2019 welcomed 13,000 attendees, up 40% from the prior year.

Systems that use data to learn and improve from experience are getting more pilots and trials in large and medium enterprises. Here are five reasons why. Large and medium-sized enterprises will step up their use of machine learning in 2018, Deloitte Global predicts, doubling the number of implementations and pilot projects that were underway in 2017. By 2020, that number will likely have doubled again. And as enabling technologies such as machine learning APIs and specialized hardware become available in the cloud, these advances will likely be increasingly within reach for small companies as well.

Five key trends will likely cause a significant uptick in enterprise use of machine learning this year, according to Deloitte Global. Large and medium-sized enterprises will step up their use of machine learning in 2018, Deloitte Global predicts, doubling the number of implementations and pilot projects that were underway in 2017. By 2020, that number will likely have doubled again. And as enabling technologies such as machine learning APIs and specialized hardware become available in the cloud, these advances will likely be increasingly within reach for small companies as well. Machine learning is an artificial intelligence (AI), or cognitive, technology that uses data to enable systems to learn and improve from experience without being programmed explicitly.

The internet of things has been a main focus among tech companies in recent years as more manufacturers have figured out ways to integrate online connectivity into devices like cars and home appliances. But a report from the Pew Research Center and Elon University's Imagining the Internet Center finds many industry analysts are taking a largely pessimistic view toward the growth of the IoT industry. In the survey, researchers polled around 1,200 analysts, academics and industry members to get their views on the growth of IoT. While 15 percent of those polled said significant numbers of people would choose to disconnect from the IoT, the remaining 85 percent of experts said users would likely choose to further integrate into the IoT thanks both to the convenience of IoT and the difficulty in disconnecting from it. Many of those polled agreed on several broad IoT development points.

What will the world look like 20 to 25 years from now? That's the question that investors in their forties should think about when considering which stocks to buy now. While even the best prognosticators can't know for sure what the future holds, three stocks seem to be pretty good bets to survive and thrive in the decades ahead. If you're in your forties, here's why Google's parent Alphabet (NASDAQ:GOOG) (NASDAQ:GOOGL), Illumina (NASDAQ:ILMN), and Teladoc (NYSE:TDOC) could be stocks to consider. Alphabet is about a lot more than just its enormously successful Google search engine. The company claims a leadership role in many of the most important technologies for the future, including artificial intelligence, robotics, and virtual reality.