As a venture capitalist, I decided to focus on AI. Very quickly I noticed that most "AI companies" ... [ ] had very little "AI" (real technology) or very little "company" (real business). I first heard the words "deep learning" in 2010 on a midnight run around Stanford's Lake Lagunita. My running partner told me about the budding technique that promised to allow machines to learn like human brains. Rather than focusing on more classical statistical models, we could take a very simple function and stack thousands, then millions, then billions, and now trillions of these "neurons" to learn and make decisions.

Tesla is now worth more than half a trillion dollars on the stock market. Last year, Elon Musk predicted that self-driving Teslas would boost Tesla's market cap to $500 billion. Although Tesla's Full Self-Driving (FSD) suite is still in a very limited beta release, Elon's prediction has come true earlier than anticipated. In fact, with the rise in market cap, Elon Musk has moved past Bill Gates in the ranking of the richest people in the world, becoming second only to Jeff Bezos. In 2019, CNBC reported that Citigroup and Goldman Sachs, who just recently announced that Tesla being added into the S&P 500 could spark an $8 billion buying spree, were on a broad investor call with Elon Musk and Tesla CFO Zach Kirkhorn.

For years, the lidar business has had a lot of hype but not a lot of hard numbers. Dozens of lidar startups have touted their impressive technology, but until recently it wasn't clear who, if anyone, was actually gaining traction with customers. This story originally appeared on Ars Technica, a trusted source for technology news, tech policy analysis, reviews, and more. Ars is owned by WIRED's parent company, Condé Nast. This summer, three leading lidar makers have done major fundraising rounds that included releasing public data on their financial performance.

For years, the lidar business has had a lot of hype but not a lot of hard numbers. Dozens of lidar startups have touted their impressive technology, but until recently it wasn't clear who, if anyone, was actually gaining traction with customers. This summer, three leading lidar makers have done major fundraising rounds that included releasing public data on their financial performance. The latest lidar maker to release financial data is Ouster, which announced a $42 million fundraising round in a Tuesday blog post. That blog post also revealed a striking statistic: the company says it now has 800 customers.

As corporate demands on data analysis and business insight get more complex and intense, the need for technology solutions and services that turn companies into intelligent enterprises is becoming paramount. Artificial intelligence and machine learning represent tremendous opportunities for partners to turn that plan into reality. Businesses want to make better use of their data, achieve outcomes faster and with less risk. SAP has committed to helping every customer become a better, smarter business and we will rely on our partner ecosystem of trusted business and technology providers to do so. Partners adept in machine learning and artificial intelligence will maintain a distinct competitive advantage.

The issue of artificial intelligence is no longer an unknown. We do not need to hypothesise on its inevitable coming. We know that it will come. We now know that it is going to be revolutionary. We also know about the fears of AI putting millions of people out of work.

When Artificial Intelligence (AI) was just science fiction, nobody thought it would become a real force in the business world. But nearly 50 years after Hal in "2001: A Space Odyssey," fantasy has morphed into a positive reality, and AI is now a business game-changer. While AI is not yet the omniscient (or ominous) presence it was in "2001," the facts are that IT management can help business partners in sales and marketing be more successful by implementing AI solutions, and here is an example of one that is easy to slot right in and show immediate value: Conversica. Conversica is the leader in conversational AI for business, because we are truly at the vanguard of deploying AI to help businesses find customers and drive revenue. Friendly, persistent, conversation-based AI is the perfect tool for following up on sales leads that would otherwise be left to die, with the true value of AI-enabled sales being that it drives greater ROI from marketing and sales programs.

This article was first published in Real Business. As the Taylor report on employment in the modern economy highlighted, our workplaces are changing rapidly. And some of the biggest drivers of that change are automation, robots and artificial intelligence. The arrival of business-orientated automation, robots and artificial intelligence can take on tasks we thought only humans could – but it will present real challenges. There will be a very direct impact on some individuals who will need to acquire different skills or will have to face the harsh reality of ceasing to be employable. That means employers will need to re-think current approaches to talent identification, training and workforce planning.

According to global consulting firm Accenture, intelligent automation powered by machine learning processes is 2016's biggest tech trend. For tech giants like Amazon and Google, machine learning has long been central to their operations - the most famous example being Amazon's recommendation engine, which many see as having been the key to its success. Such technology has huge implications for organizations across all industries though, and the wealth of data that companies now hold, along with the rise in affordable products like Microsoft Azure ML and IBM Watson, mean that they are rushing to adopt it.

For anyone that thinks artificial intelligence (AI) belongs firmly in the future, it's worth taking a moment to remember that the technology has its roots squarely in the past; 60 years in the past to be precise. Six decades ago, delegates gathered at the first Dartmouth Conference to hear about an exciting new world of "artificial intelligence". It's said amongst IT historians that this was the first time the term was ever used. Today there are a lot of practical applications for AI but many people can't imagine a real world example that doesn't end with a group of crazy megalomaniac robots taking over the planet and wiping out humanity. But, as with many scientific advances, the reality is a lot simpler, modest and, dare we say, down-to-earth. Take Facebook's recent announcement about launching a range of chatbots.