SAN FRANCISCO -- When Google kicks off its annual get-together for software developers on Wednesday, expect to hear about the two major trends shaping the future of the technology industry: artificial intelligence and virtual reality. Thousands will descend on Mountain View, Calif., the first time the tech giant is holding the I/O conference in its hometown. Google's conference, sandwiched between Facebook in April and Apple in June, is vying to put on the greatest show on earth for software developers. For weeks, workers have been constructing a Google-themed park to immerse developers in the artificial intelligence-powered future that Google envisions.The outdoor venue, the Shoreline Ampitheatre, is most famous for showcasing the talents of Neil Young, The Who and Metallica. For I/O, the master of ceremonies is Sundar Pichai, Google's newly minted chief executive who will look to dazzle developers with a demo-packed keynote.

Last week, NVIDIA released its first-quarter fiscal 2017 report, which included some impressive results. The graphics-processor maker posted Q1 revenue of 1.3 billion, an increase of 13% year over year, and non-GAAP earning per share were up 39% from the year-ago quarter to 0.46. Wall Street analysts had been expecting revenue of around 1.26 billion and EPS of 0.41. NVIDIA co-founder and CEO Jen-Hsun Huang said the revenue and earnings growth were spurred on by all of the key segments of its business. "We are enjoying growth in all of our platforms -- gaming, professional visualization, datacenter and auto," Huang said in a press release.

Law school, the default location for America's brightest unemployed Liberal Arts graduates and the worst decision a 20-something can make in the modern era just became an even worse bargain, if that's possible. We're not talking about a surge in LSAT applicants, beginning in 2008, that led to the creation of InfiLaw Corporation scam-law-schools like Charlotte, Florida Coastal, or Arizona Summit, the latter of which boasts an average bar passage rate of below 31% and an average cost of attendance exceeding 250,000. We are not even speaking about a profession that requires the completion of at least seven years of college,followed by an expensive test and an invasive background check, just for the benefit of staring down the barrel of a 15.5 percent unemployment rate and roughly 200,000 in non-dischargeable student debt. One might even guess that we're talking about how recent studies show that over 40% of law school students suffer from clinical depression, with those unhappy figures only becoming worse as graduates enter a profession with a suicide rate nearly ten times above the national norm. Instead, we are talking about the latest and greatest idea among the old-timers; those old ones who have already won the legal profession lottery, allowing them to seize an upper-middle class lifestyle after matriculating from law schools referred to as'third-tier toilets,' or attending bastions of prestigious opportunity, like Harvard and Yale.

Paging HAL: What Will Happen When Artificial Intelligence Comes to Radiology? The myth of Hephaestus' golden handmaidens illustrates mankind's centuries-long fascination with artificial intelligence (AI). The god of the forge created his handmaidens, who could talk and perform even the most difficult tasks, to assist him in his labors, and many people have since speculated about the possible uses of AI and the forms it might take. More recently, noted scientists and futurists, such as Ray Kurzweil; Stephen Hawking, CH, CBE, FRS, FRSA; and Elon Musk, have discussed, debated, and dissected the possibilities and pitfalls of AI. With many AI advances coming in the past few years, some people are beginning to wonder whether it will eventually replace radiologists.

As Wired reports, Google's team "inspired" the poetry by giving the system two sentences from the books it had read and telling it to reproduce a new sentence based on the data set of 11,000 books it had just plowed through. "come with me," she said. "talk to me," she said. "don't worry about it," she said. While it might not win any Pulitzers at the moment, the neural network's writing homework could eventually lead to smarter, more human-seeming chatbots.

There's still a long way to go before complex human traits like humor can be properly emulated by artificial intelligence, but Alphabet Inc. is already starting to inject wit into the research effort. The company last week published a machine learning model called "Parsey McParseface" that can automatically map out the linguist structure of any English-language text. The algorithm, which is hailed as the most accurate of its kind yet, was created using a neural networking system that became available on GitHub at the same time. Alphabet hopes that its contribution will ease the development of virtual assistants and other modern applications that deal with a lot of human-generated information. Equally importantly for the search giant, the move will also cement its position in the open-source machine learning community, which has emerged as a key focus area for the web-scale crowd.

This is the another post of the series: How to build your own algotrading platform. Machine learning and trading is a very interesting subject. It is also a subject where you can spend tons of time writing code and reading papers and then a kid can beat you while playing Mario Kart. Machine learning algorithms are algorithms where a machine can identify patterns in your data. Yeap, it is that simple.

Thanks to machine learning, the page you see when you log-on to Amazon.com is likely very different from the one I see. Advertising, product recommendations, and special deals are all tailored to our unique customer profiles based on historical browsing trends and buying behavior. Online retailers like Amazon were among the first users of customer data collection and analysis for improving services and personalizing the shopping experience, and they've become so skilled some sites might even be able to predict what we will purchase before we even know what we're looking for. Advancements in digital technologies have driven a paradigm shift in the way businesses interact with their customers, with touchpoints increasingly moving to digital mediums. Because of the limited opportunities to satisfy customers on a person-to-person level, machine learning is now in widespread use by a variety of modern enterprises as a way to enrich customer experiences, create more personalized and customer-centric interactions, and offer seamless omnichannel communications. Machine learning goes a step beyond Big Data analytics, where machines employ advanced algorithms to autonomously adapt and learn from previous experiences, and therefore emulate the thought process behind human decision-making.

Google is promoting natural language understanding with the open-sourcing of SyntaxNet, a neural network framework, and Parsey McParseface, an advanced parser for English text. Implemented in Google's open source TensorFlow machine intelligence library and released this month, SyntaxNet provides the code needed to train natural language understanding (NLU) models on your data along with the Parsey McParseface parser for analyzing English text. "Parsey McParseface is built on powerful machine learning algorithms that learn to analyze the linguistic structure of language and that can explain the functional role of each word in a given sentence," said Slav Petrov, Google senior staff research scientist. The project arose out of Google's pondering of how computers can read and understand human language in order to process it in intelligent ways. Accessible on GitHub, SyntaxNet serves as a framework for a syntactic parser, a key first component in many NLU systems, Petrov said.

Last week, NVIDIA (NASDAQ:NVDA) released its first-quarter fiscal 2017 report, which included some impressive results. The graphics-processor maker posted Q1 revenue of 1.3 billion, an increase of 13% year over year, and non-GAAP earning per share were up 39% from the year-ago quarter to 0.46. Wall Street analysts had been expecting revenue of around 1.26 billion and EPS of 0.41. NVIDIA co-founder and CEO Jen-Hsun Huang said the revenue and earnings growth were spurred on by all of the key segments of its business. "We are enjoying growth in all of our platforms -- gaming, professional visualization, datacenter and auto," Huang said in a press release.