Staging is serious business in presidential politics. Every detail--from the sign on the lectern to the demographics of everyone behind the candidate to (on one bizarre occasion this cycle) the raw slabs of meat dressing the set--is meant to convey who the candidate is and what the candidate stands for. So you can learn a lot juxtaposing the optics of the campaign speeches Hillary Clinton and Donald Trump gave last week on the future of the economy. While Clinton spoke from the center of a tech hub in Denver, surrounded by millennials tapping away on MacBooks, Trump addressed a crowd inside a scrap metal factory in a Pennsylvania steel town, standing before a wall of crushed aluminum cans. Before either candidate spoke, they'd cast two opposing visions.

Everything we know about the face recognition systems the FBI and police use suggests the software has a built-in racial bias. That isn't on purpose--it's an artifact of how the systems are designed, and the data they are trained on. Law enforcement agencies are relying more and more on such tools to aid in criminal investigations, increasing the risk that something could go wrong. Law enforcement agencies haven't provided many details on how they use facial recognition systems, but in June the Government Accountability Office issued a report saying that the FBI has not properly tested the accuracy of its face matching system, nor that of the massive network of state-level face matching databases it can access. And while state-of-the-art face matching systems can be nearly 95 percent accurate on mugshot databases, those photos are taken under controlled conditions with generally coöperative subjects.

It is Wednesday, July 6. A 300-pound robot is the new security guard at Uber's inspection lot in San Francisco. Here's what else is happening in the Golden State: When undercover CHP officers shot at suspects in a moving car this weekend, they used a tactic that's been outlawed in many major cities because experts believe it's too dangerous. They fired at a moving car. "Only a fool thinks a … bullet is going to stop a 3,800-pound car. Nobody is really shooting at the vehicle, they're shooting at the driver," said Sid Heal, a retired Los Angeles sheriff's commander and chairman of strategy development for the National Tactical Officers Assn.

In last month's blog I talked about keeping your team innovative. One of the key tenets of an innovative team is the concept of moonshots or "10x Thinking" or audacious goals. In a "moonshot economy," while a breakthrough can mean the start of a new industry leader, it can also mean the death of an industry stalwart. First, let's take a look at some previous moonshots and how they've impacted various industries and the world. The first is, of course, the great Space Race.

The NHS is pairing up with Google's artificially intelligent image software DeepMind for a new medical research partnership that could play a "big role in tackling avoidable sight loss." Specialists at the NHS-funded Moorfields Eye Hospital in London will use DeepMind, the internet giant's machine learning project, to research whether the technology can help detect and prevent eye diseases and blindness. DeepMind will be applied to one million anonymous eye scans to look for early signs of eye conditions that humans might miss such as macular degeneration and retinal conditions caused by diabetes. The end goal of the research is to create a more efficient method by which to analyse data and come to an earlier diagnosis for patients. The number of people suffering from sight loss in the UK is predicted to double by 2050, and the project marks Google's first machine learning collaboration with healthcare specialists.

Google-owned DeepMind has expanded its collaboration with the UK's National Health Service (NHS), announcing a research partnership today with Moorfields Eye Hospital NHS Foundation Trust in London -- its second publicly confirmed foray into working with the NHS. But this time the project is being explicitly badged as medical research, and DeepMind will be applying AI machine learning algorithms to the data -- so that's also a first. Although the company has been public about its ambitions to apply AI to health data before now. The Moorfields partnership is focused on two specific sight-loss causing conditions: diabetic retinopathy and age-related macular degeneration (AMD), which DeepMind notes collectively affect more than 625,000 people in the UK and more than 100 million people worldwide. The stated aim is to investigate whether machine learning algorithms can automate the analysis of the digital eye scans that are typically used to diagnose the two conditions.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

NHS eye hospital Moorfields has announced it is working with DeepMind -- an artificial intelligence research lab acquired by Google in 2014 for a reported 400 million -- in a bid to identify people who are likely to lose their sight as a result of an eye disease. Through the medical research partnership, Moorfields will investigate whether DeepMind's AI technology can be used to help spot early signs of eye conditions that human eye care experts might miss. In order to determine whether DeepMind's AI technology is useful for diagnosing eye conditions, Moorfields is applying the company's algorithms to one million anonymous OCT (Optical Coherence Tomography) scans. The aim is to determine whether the algorithms can learn to spot early signs of age-related macular degeneration and sight loss that occurs as a result of diabetes. Mustafa Suleyman, Google DeepMind cofounder and head of DeepMind Health, told Business Insider that he wants DeepMind's AI to understand the structure and nature of eye scans "well enough to be able to try to predict in advance which ones indicate that a patient may be at risk to a particular kind of eye disease." The algorithms that DeepMind builds are known as machine learning algorithms because they have the ability to learn through training without being explicitly programmed.

Sam Altman, the president of top startup mentorship and investment program Y Combinator, thinks venture capitalists like himself have gotten off too easily, tax-wise -- so he's putting the difference into improving the world. "I donate up to the tax amount I think I should pay," Altman told BuzzFeed News' Nitasha Tiku. The fiscal issue Altman is rebelling against is the "carried interest" tax for hedge fund managers and VCs. It's one of Wall Street's favorite loopholes, and one that President Barack Obama has long railed against. Basically, it allows these fund managers to take the incentive portion of their fees -- which they earn based on the gain in value of the investments they made for clients -- and classify that income as capital gains rather than ordinary income, thereby paying a much lower tax rate.

When the Raspberry Pi computer was first launched in 2012 to promote the teaching of computer science, its creators probably didn't imagine the 35 device would one day take on a professional fighter pilot in a dogfight--and win. But that is exactly what a doctoral graduate at the University of Cincinnati set out to do when he built a Pi-powered artificial intelligence pilot. The AI, dubbed ALPHA, went up against retired United States Air Force Colonel Gene Lee in a series of simulated battles, beating Lee in every single engagement. Lee described ALPHA as "the most aggressive, responsive, dynamic and credible AI I've seen to date." ALPHA has gone on to defeat other expert fighter pilots in what is being hailed as a significant breakthrough in unmanned flight.