Earlier this year, Andreessen Horowitz investor Chris Dixon noted the challenge investors face in helping to groom promising AI startups, given how quickly Facebook, Google, and Amazon are bringing aboard related talent. Dixon noted, for example, that Wit.ai, a Y Combinator startup that built voice-activated interfaces that Facebook bought and which now powers its Messenger platform, was only in Andreessen Horowitz's portfolio for a few months when Facebook bought it. But firm co-founder Marc Andreessen said on stage at Disrupt today that the firm is beginning to see things swing in the opposite direction. "Two years ago, it seemed like four or five companies were hoovering up all the talent . . . I think something like 1,500 people over four years [were involved in] building Alexa," the technology that powers Amazon's voice-controlled home computer Echo.

All-natural and organic are familiar terms to consumers, and anything artificial has become anathema to many. Unless we're talking artificial intelligence – or AI – then investors should be hungry to learn as much as possible about a technology that is becoming as ubiquitous as organic tofu. The vast majority of nearly 2,000 experts polled by the Pew Research Center in 2014 said they anticipate robotics and artificial intelligence will permeate wide segments of daily life by 2025. A 2015 study covering 17 countries found that artificial intelligence and related technologies added an estimated 0.4 percentage point on average to those countries' annual GDP growth between 1993 and 2007, accounting for just over one-tenth of those countries' overall GDP growth during that time. Interesting numbers – but just what is artificial intelligence?

Ben Dickson is a software engineer and the founder of TechTalks. As artificial intelligence and machine learning mature and manifest their potential to take on complicated tasks, we've become somewhat expectant that robots can succeed where humans have failed -- namely, in putting aside personal biases when making decisions. But as recent cases have shown, like all disruptive technologies, machine learning introduces its own set of unexpected challenges and sometimes yields results that are wrong, unsavory, offensive and not aligned with the moral and ethical standards of human society. While some of these stories might sound amusing, they do lead us to ponder the implications of a future where robots and artificial intelligence take on more critical responsibilities and will have to be held responsible for the possibly wrong decisions they make. At its core, machine learning uses algorithms to parse data, extract patterns, learn and make predictions and decisions based on the gleaned insights.

Mark Zuckerberg and his wife, Priscilla Chan, have laid out plans to invest $3bn over the next 10 years with the not insignificant goal of tackling all diseases. "Can we cure, prevent or manage all disease by the end of this century?" The Chan Zuckerberg Initiative will focus on some of the world's biggest killers, including heart disease, cancer, infectious diseases and neurological diseases. One of its biggest investments is to be a $600m "Biohub" at UCSF, which will bring together scientists and engineers from Stanford, Berkeley and UCSF – who haven't collaborated in this way before – to develop tools to treat diseases. The second focus will be transformative technology, all of which will be made available to all scientists everywhere. "Throughout the history of science, most of the major scientific breakthroughs have been preceded by some new tool and technology that allows you to see in new ways," explained Zuckerberg.

Anthony Foxx waits for the countdown, then hits the plunger. The catapult releases its bungee cord, slinging the drone from to a standstill to 50 mph in half a second. The drone spins up its twin propellers and flies a few hundred feet up, circling overhead. "That's amazing," Foxx says, as the UAV drops its package within a few feet of the practice delivery zone, then belly flops onto a brown landing pad that resembles the base of a jumping castle. During the closing months of his four-year run as US Secretary of Transportation, Foxx has come to California on a fact finding mission.

Behavioural change is a very tricky thing. We humans are so fickle. We see a bright shiny wearable device that can track our every move and we think it's our "silver bullet", a "ticket" to achieving our health and fitness dreams. Only for guilt to set in, as after a short time, the wearable device winds up in our top drawer. We knew the fitness data was great, but we really didn't know what to do with it. The truth is, behaviour change requires much more than data. Many programs have realized the magnitude of the problem and created incentive programs to reward people for being active, so they get a small pay-off on the road to achieving fitness. But in spite of these rewards, the drop-out rate remains problematic.

Paul Daugherty, Accenture's CTO talks about why AI is the future of business at the Artificial Intelligence Summit 2016 in San Francisco. He gives insight on new quantitative research released at AI Summit conducted by Accenture and Frontier Research answering the question; how will AI impact business?

Analytics and Artificial Intelligence ensure that work is completed in the optimum way Operating performance is tracked in detail in real time. Automatically distributes work for completion according to parameters set by you – Like an aeroplane's autopilot navigation along a fight path Identifies patterns in workload, operational costs and user behaviour to highlight optimum performance, improvement opportunities and areas for review Automatically map your business processes as they have been performed One of the biggest challenges facing organisations today is the hype around "Straight Through Processing" (STP) Typically, many business processes do not provide a strong ROI when converting to STP Omniflow's Artificial Intelligence will identify processes and tasks where STP will provide maximum ROI and then automate only the steps where ROI is evident In partnership with Process Automation Group, P&N Bank recently implemented the Omnifow Digital Workspace which has transformed the approach and outputs of our Operations Team. With Omniflow, we have real-time visibility of the workload and have achieved significant member experience and productivity improvements. The system is easy to use and has gained team member support resulting in benefit realisation within days of implementation.

Hedge funds have been in the doldrums and face mounting pressure to justify their fees. Will artificial intelligence come to the rescue? A growing number of hedge funds are putting money behind the idea that a branch of AI called machine learning could provide a way to get back on top. A software program that searches for patterns in more data than even the most sleep-deprived junior analyst could examine, and then tests its hypotheses against even more data. What can satellite shots of mall parking lots tell you when combined with in-store sales data?

What would you get if you cross ibuprofen with aspirin? No one is sure, but a team of MIT researchers headed by Alán Aspuru-Guzik has developed an artificial intelligence program that could provide an answer to this by recommending a molecular structure that amalgamates properties of both the medications. The program could assist in finding new drug compounds. So far, researchers have relied on software that crawls through huge pools of candidate molecules with the help of rules crafted by chemists to predict or identify useful structures. This technique often requires humans, the precision of simulations, and the necessary processing power.