Recently, I've curated a list of 50 Finnish startups in the field of AI & Machine Learning for those who are looking for business partners or companies to invest in. If you are an international investor who wants to connect with one of the startups, feel free to drop me a message. I can make the intro and provide the companies' investor pitch deck to you if it is available. You can also use Finder.fi to check the company's revenue development. If you are an ambitious entrepreneur (based in Finland) who is working on the next world-changing idea and is looking for funding, let's meet! I'll be happy to discuss how we can help you with the fundraising process (for free). Most of the following information is from the company website. But if you've spotted an error, please let me know and I will revise accordingly. "AISpotter has developed a time-saving, fast service for coaches all around the world. Our goal is to combine high-end technology and sports of any kind. With real-time analysis, coaches and teams are given the power to be one step ahead in team development." "We've taken over 30 years of recognized University of Oulu Machine Vision Group technology and adapted it to improve your sports game. By combining state-of-the-art machine learning and computer vision in our unique way, we provide automatic and fast analysis service for your game."

Researchers, companies and countries around the world are racing to explore -- and exploit -- the possibilities of artificial intelligence technology. China is working on an extremely aggressive multi-billion-dollar plan for government investment into AI research and applications. The U.S. government has been slower to act. The Obama administration issued a report on AI near the end of its term. Since then, little has happened -- until a Feb. 11 executive order from President Donald Trump encouraging the country to do more with AI.

Researchers, companies and countries around the world are racing to explore -- and exploit -- the possibilities of artificial intelligence technology. China is working on an extremely aggressive multi-billion-dollar plan for government investment into AI research and applications. The U.S. government has been slower to act. The Obama administration issued a report on AI near the end of its term. Since then, little has happened -- until a Feb. 11 executive order from President Donald Trump encouraging the country to do more with AI.

Researchers, companies and countries around the world are racing to explore -- and exploit -- the possibilities of artificial intelligence technology. China is working on an extremely aggressive multi-billion-dollar plan for government investment into AI research and applications. The U.S. government has been slower to act. The Obama administration issued a report on AI near the end of its term. Since then, little has happened -- until a Feb. 11 executive order from President Donald Trump encouraging the country to do more with AI.

Iterative Lean Startup principles are so well understood today that an minimum viable product (MVP) is a prerequisite for institutional venture funding, but few startups and investors have extended these principles to their data and AI strategy. They assume that validating their assumptions about data and AI can be done at a future time with people and skills they will recruit later. But the best AI startups we've seen figured out as early as possible whether they were collecting the right data, whether there was a market for the AI models they planned to build, and whether the data was being collected appropriately. So we believe firmly that you must try to validate your data and machine learning strategy before your model reaches the minimal algorithmic performance (MAP) required by early customers. Without that validation -- the data equivalent of iterative software beta testing -- you may find that the model you spend so much time and money building is less valuable than you hoped.

As every entrepreneur will know, securing that first round of seed capital is often the most crucial step in getting any business off the ground. And for their part, seed investors play a crucial role as tech influencers or tastemakers, often backing a trend years before it becomes mainstream. But what do these European tech tastemakers of today think is coming tomorrow? Artificial intelligence is the number one sector that seed investors in Europe are obsessing over, with a whopping 70% saying they're most excited about what's going on in the space. Mosaic Ventures, which has backed companies like period-tracking app Clue and crypto wallet Blockchain, this morning published the figures as part of an extensive study into the sentiment of 60 top European seed funders.

At some point in the future, while riding along in a car, a kid may ask their parent about a distant time in the past when people used steering wheels and pedals to control an automobile. Of course, the full realization of the "auto" part of the word -- in the form of fully autonomous automobiles -- is a long way off, but there are nonetheless companies trying to build that future today. However, changing the face of transportation is a costly business, one that typically requires corporate backing or a lot of venture funding to realize such an ambitious goal. A recent funding round, some $128 million raised in a Series A round by Shenzhen-based Roadstar.ai, In short, not as many as you'd think.

A few years ago, Teslas driving down Sand Hill Road couldn't kick up a pebble and somehow not hit a founder--typically fresh out of a PhD program--talking about their new machine learning startup. "Machine learning" was the "blockchain" of its day. However, it appears as though venture funding into companies specifically focused on machine learning and AI and its applications has begun to level off, at least in the US. But that may not be such a bad thing. Before we discuss why that could be the case, let's take a look at the numbers.

UPDATED, Feb. 5, 11:38 a.m.: Just 20 years ago, fax machines were in wide use and most people didn't have cell phones. Fast forward to today, and smartphones are inescapable and personal hotspots are tucked into everyone's pockets. The real estate industry has seen its own advances during that time, with drones debuting on construction sites and prefabricated modular apartments now being snapped together easily onsite. Today, for example, it's virtually impossible to ignore the white-hot Bitcoin craze and barrage of news about how cryptocurrencies and blockchain could revolutionize real estate. But the next big tech revolution in New York's trillion-dollar real estate business could be far more disruptive. In the near future, the industry could see smart buildings fully controlled by technology, robots taking the place of construction workers and New York City skyscrapers being made by 3D printers. Meanwhile, property leases, loans and investment transactions may be handled without any human involvement, observers say, thanks to artificial intelligence. The question everyone is now mulling: After decades of sparse innovation, is real estate finally in for a major wakeup call from the tech sphere? "I only see the pace of change accelerating," said James Barrett, chief innovation officer at Turner Construction, one of the largest construction management firms in the country. This month, on the heels of the bustling CES tech conference in Las Vegas, The Real Deal broke down some of the innovations with the greatest potential to upend the real estate industry -- from artificial intelligence and virtual reality to people-tracking beacons and blockchain.

Venture capital isn't a monolith, but startup investors are compared to lemmings for a reason. Once a trend gets hot, every firm needs to make a play, or come up with a good excuse for missing out. Investors continue to aggressively pour money into startups. As of the third quarter, US investors were on track to match or exceed 2016's $69 billion in investments, according to the National Venture Capital Association and Pitchbook. For startups, riding a trend such as artificial intelligence can be the difference between a hot round of funding and no investor interest. Founders have spent the last year throwing terms like blockchain, neural network, and machine learning into their pitch decks in hopes of attracting investment.