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) …
AI and machine learning algorithms require data. But the bulk of that data is of no use if it isn't first labeled by human annotators. This predicament has given rise to a cottage industry of startups, including Scale AI, which recently raised $100 million for its extensive suite of data labeling services. That's not to mention Mighty AI, Hive, Appen, and Alegion, which together occupy a data annotation tools segment that's anticipated to be worth $1.6 billion by 2025. CloudFactory is yet another vying for attention.
Google Chief Executive Officer Sundar Pichai was in Tokyo on Tuesday to inaugurate the move of the company's Japanese head office to an expansive new complex in the Shibuya district. Taking up the majority of the gleaming new 35-floor Shibuya Stream building, Google has put its name on the building and dedicated two floors to the newly launched Google for Startups Campus, which is its seventh in the world and second in Asia, after Seoul. Agnieszka Hryniewicz-Bieniek, the director of Google for Startups, said the company will run an accelerator program early next year to select 12 startups looking to scale up their work on artificial intelligence and machine learning, both critical aspects of Google's current and future operations. She also stressed the importance of inclusiveness at an event where the Wi-Fi password was BuildInclusiveTeams. "We would like Campus Tokyo to support women founders," she said, adding that Google is proud that 37 percent of its campus participants are female entrepreneurs, a higher proportion than in the wider startup ecosystem. "So when they go to the next stage of growth, we're behind them, we're supporting them."
Canada has received more than its usual share of attention for its AI capabilities. The country was either prescient or lucky in continuing to fund neural networks research when the US retreated from it in the 1970s and 80s. As a result, Canadian researchers like Geoffrey Hinton, Yann LeCun, and Yoshua Bengio pushed forward the methods we now call "deep learning." These three researchers won the 2018 Turing Award--often called the Nobel equivalent for computer science. Canada is also known in AI for its collegial, public/private ecosystems.
Will artificial intelligence (A.I.) and machine learning carve up the tech industry into "haves" and "have nots"? That's the thesis presented by a recent article in The New York Times, which suggests that, while ultra-monetized companies such as Google and Facebook can fund as much A.I. research as they need, academic institutions and smaller firms are being left behind. "The huge computing resources these companies have pose a threat--the universities cannot compete," Craig Knoblock, executive director of the Information Sciences Institute at the University of Southern California, told the newspaper. The Times points to OpenAI, which launched as a nonprofit designed to prevent A.I. from being used in terrible and unethical ways, as an example of this trend. OpenAI has since evolved into a "capped" for-profit company, and reportedly plans to use any revenues to fund its computing infrastructure.
It's no secret that big tech companies like Amazon (AMZN), Microsoft (MSFT), and Alphabet (GOOG), the parent company of Google, are investing in digital healthcare. The market opportunity is pretty enticing when you consider that the U.S. alone spent $3.65 trillion on healthcare just last year. Google made the latest headline-grabbing move when it announced that it would buy wearables-maker Fitbit (FIT) in a deal valued at $2.1 billion. Analysts have noted that the acquisition is part of the company's overall strategy to build an ambient intelligent system where Google is omnipresent. Another motive behind the purchase – pending regulatory approvals – is that Fitbit gives Google access to a treasure trove of healthcare data that it can feed to its London-based AI lab DeepMind or its life sciences subsidiary Verily, which is already collaborating on at least one AI healthcare device for remote patient monitoring.
AI is in full gold rush mode. Every day we hear headlines of AI companies raising vast sums of capital to give them the resources to prospect the veins of AI gold. The money is flowing to these new frontiers. In the US venture capital funding for AI grew 72% year over year to a whopping $9.3B in 2018. Dataminr, a New York based AI and machine learning company that makes sense of news and information in real time, raised US$392 million in 2018, for example.
Our post on the 100,000 registered customers milestone this summer included an infographic of sample use cases being explored by BigML users, which naturally span many different sectors and industries. Today, we'd like to start a series of posts that further highlight a subset of those business problems to give our readers some clues on how a comprehensive platform as ours can be utilized in different business contexts in case they're considering new Machine Learning solutions. There are many ways to organize use cases, e.g., by industry, function, geography. In this post, we will focus on startups and SMBs as we give you a glimpse of the motivation behind solving each reference use case. Startups and SMBs have good reasons to prefer the BigML platform because it lets them to affordably step into Machine Learning with ample room to further scale efforts as data volumes and the number of use cases implemented grow over time.
By 1433, the Chinese admiral Zheng He had already sailed from China to India, Indonesia, and even Africa on caravels twice as large as those Christopher Columbus used 59 years later for his fateful journey. China could have been the country to discover America. Instead, its government surprisingly decided to put an end to its naval activities and burn its entire fleet of ships, indirectly allowing Spain to conquer America and bring prosperity to Europe. It took more than 5 centuries for China to recover from this political decision. What could make such an advanced country deliberately turn away from its future?
We meet monthly to support the local startup scene. This month 1 Million Cups Louisville is at the new Story Louisville space on 900 E. Main Wednesday, November 20th at 8:00 a.m. We're still caffeinated by the Kauffman Foundation and our events are always FREE! There's no question that artificial intelligence is moving quickly in healthcare. But voice first tech for patients is just one side of the communications coin. Let's face it, hospitals are one of the most notoriously complex environments.
According to a recent study conducted by Forrester Research, waiting in the checkout line is the top complaint among U.S. grocery, mass-merchandise, and convenience store shoppers. Mega-retailer Amazon and a quartet of well-funded retail technology startups -- Zippin, Standard Cognition, Grabango and Trigo -- believe they have the solution to the problem: Checkout-free stores powered by various technologies that enable shoppers to walk into the store, grab what they want off the shelves and just walk out. Autonomous checkout, another term for checkout-free, is becoming one of the hottest areas of retail investment today. It comes as the convenience expectations of today's Amazon-shopping, Grubhub-ordering, Uber-hailing consumers are ever-increasing, and informing their in-real-life (IRL) shopping demands. Brands are responding in kind, delivering digital services aimed at automating mundane tasks -- in this case, the checkout process -- so much so that the result is meant to feel "automagical," according to trend forecasting firm TrendWatching.