The classic guide for entrepreneurs preparing a pitch is Sequoia's Business Plan Template. This post aims to be a mere addendum to that in the age of machine learning. Why do investors spend so much time focusing on'differentiation'? The job of an investor is to allocate money to its best use. Investors shouldn't allocate money to a company unless it is crystal clear that the company is the best one to solve a particularly valuable problem.

I first met Pepper in 2014, a human-shaped robot at a mobile store of Akihabara district in Tokyo. Although our conversation quickly reached some limits by the fact that he (it?) could only speak Japanese at the time, I sympathized with what his creator Aldebaran (a French company now part of the Softbank Japanese conglomerate) defines as a genuine day-to-day companion, whose number one quality is his ability to perceive emotions and adjust his behavior to your mood based on your voice, face expression and words you use. To-date, 10,000 Pepper robots have been sold mostly to Japanese homes. One third of them are used as an attraction to surprise customers and inform them. Nestlé is planning on equipping more than 1,000 Nescafé sales outlets in Japan.

Google artificial intelligence project DeepMind is building software to trawl through millions of patient records from three NHS hospitals to detect early signs of kidney disease. The project raises deep questions not only about data protection but about the ethics of artificial intelligence. But these are not the obvious questions about the ethics of autonomous, intelligent computers. Computer programs can now do some things that it once seemed only human beings could do, such as playing an excellent game of Go. But even the smartest computer cannot make ethical choices, because it has no purpose of its own in life.

Harvard University has been awarded 28 million ( 19m) to investigate why brains are so much better at learning and retaining information than artificial intelligence. The award, from the Intelligence Advanced Projects Activity (IARPA), could help make AI systems faster, smarter and more like human brains. While many computers have a comparable storage capacity, their ability to recognise patterns and learn information does not match the human brain. But a better understanding of how neurons are connected could help develop more complex artificial intelligence. Most neuroscientists estimate that the'storage capacity' for the human brain ranges between 10 and 100 terabytes, with some evaluations putting the number at close to 2.5 petabytes.

The Big G wants its app to be more conversational, so it's feeding a neural network with steamy sex scenes and hot encounters. According to Buzzfeed News, the network has been devouring a collection of 2,865 romance novels over the past few months, with saucy titles like Fatal Desire and Jacked Up. It seems to be working too: it was able to write sentences resembling passages in the books during the researchers' tests. While the AI now has what it takes to become an erotic novelist, the team's real goal is to use its newly acquired conversational tone with the Google app.

The evidence of our displacement by machines is sketchy, and we should be able to adjust to the new technological era if we put our minds to it. OPINION: It is now widely accepted that technological advances, especially ones that make machines more like humans - such as robotisation or artificial intelligence - are putting people out of work and will only destroy more jobs in the future. The wealth will accrue to those who own the machines, not to what's known as the middle class today. There's some good news for humans, though: The evidence of our displacement by machines is sketchy, and we should be able to adjust to the new technological era if we put our minds to it. Eric Brynjolfsson and Andrew McAfee of the Massachusetts Institute of Technology labelled this "the great decoupling": according to them, advances in productivity, mainly driven by the development of digital technology, and the resulting economic growth, no longer cause employment and workers' incomes to rise.

When it comes to sports teams, marketing is everything. You have to sell tickets, merchandise and get the deals for TV coverage, though the latter is usually covered by a deal with the league. Now the NBA's Portland Trail Blazers is teaming up with Microsoft in an effort to obtain the data it needs to increase its revenue. To accomplish that goal the team is turning big data and the power of the Cortana Intelligence Suite, Microsoft's digital assistant. The goal is selling more season tickets, a tough sell given that most ticket buyers tend to not change their habits from year to year according current data.

The rap on eBay's website is that it's too messy, forcing users to pick through page after page of listings to find what they really want. Plenty of customers just give up and head to Amazon instead. The good news is that eBay knows this is a problem and is working to fix it. The bad news is that eBay on average hosts 900 million listings -- from new ink cartridges to one-of-a-kind porcelain dolls -- making sorting all this stuff a humongous job. As part of its push to offer up more relevant products to shoppers, eBay on Thursday said it agreed to purchase Sweden-based Expertmaker, a 10-year-old software firm specializing in artificial intelligence and machine learning to help organize and analyze huge sets of data.

When it was revealed that Google's London-based company DeepMind would be able to access the NHS records of 1.6 million patients who use three London hospitals run by the Royal Free NHS trust – Barnet, Chase Farm and the Royal Free – it rang alarm bells. Not just because Google, a sprawling octopus of a company with tentacles in all our lives, wishes to "organise the world's information". Not just because patients are unlikely to have consented to Google having this information. The issue for many is the intertwining of these concerns with the idea of artificial intelligence (AI). DeepMind is no ordinary company.

Some readers were skeptical of the idea that A.I.'s interests could ever correspond with our own, despite the work of researchers such as Stuart Russell who are trying to ensure that computers can learn to recognize what's most important to humans. As one who took such a position put it, "A.I. will likely just be a very, very smart machine and the concept of'interests' might not bear." Instead, "We should worry more about whether the interests of private and military A.I. R&D teams align with our public interests," a reader suggested. Another wrote that "terrorist groups and … enemy nation states" presented the greater risk. And others continued to hold that the real trouble is that there's no such thing as human interest per se, as did one who wrote, "We humans can't even agree on what constitutes'good' and what constitutes'evil.' "