The SIIA CODiE Awards are the premier awards for the software and information industries, and have been recognizing product excellence for over 30 years. I spoke recently with Martin Vauthier, Head of Artificial Intelligence Analytics at Enablon. Here are Martin's answers to five questions, which give you a great idea of what's happening with AI, especially regarding the use of AI in workplace safety. Artificial Intelligence is another buzzword we hear often. Sometimes there's a disconnect between how much we hear about a technological innovation, and how much it is actually used.

The age of artificial intelligence, machine learning and robotics is here, and these technologies will continue to shape our lives in the future. But the people working in these fields still don't reflect the society they are bound to change. Women make up only 22% of AI professionals worldwide, according to analysis done by LinkedIn and the World Economic Forum for its 2018 Global Gender Gap Report. In the more specialized area of machine learning, only 12% are women, based on a study done by Wired in partnership with Montreal startup Element AI. Artificial intelligence and machine learning continue to be male-dominated fields.

In the last few years, many asset-intensive organizations, particularly in the mining, power and utilities, oil and gas, and chemicals industries, have turned to industrial Internet of Things (IIoT) and cognitive technologies to help improve a critical area of their business: equipment reliability.1 Asset performance management (APM) programs, which connect data and trigger actions via systems across the business, can play a major part in driving these improvements. According to a 2018 Deloitte survey, oil and gas leaders rated the big data derived from programs such as APM as the most likely to provide the greatest business value.2 However, when asked about how digital technology can be used most effectively within their companies, those same executives ranked APM below both cost reduction in maintenance and operations as well as improvements in safety.3 This seems to reveal a pervasive and narrow view of APM that may miss the connection between asset performance, broader maintenance and operations improvements, and safety. Merely implementing APM software and digitizing existing processes is not likely to improve core operations and obtain the financial results that executive leaders desire (and investors demand).

Will AI replace your job? Artificial intelligence is more dangerous than nuclear weapons. That's according to Elon Musk, who warned against the dangers of this technology at South by Southwest in 2018. Zeb Evans is the founder and CEO of ClickUp, a company that offers project management solutions for businesses. Evans is based in San Francisco and founded ClickUp in 2017.

Whatever makes you tick, you will find it in Connected Data London 2019. Knowledge Graphs, Machine Learning and AI, Linked Data and Semantic Technology and Graph Databases are redefining how data works. Data is redefining how everything works. And Connected Data London is the go-to event for the latest developments in these key technologies. We are picking up from where we left off in 2018, connecting technologies, data, and people.

While pharma C-suite executives find themselves increasingly seduced by the promise of "digital transformation," and especially by the idea of leveraging AI, the lived, on the ground reality within virtually all pharma R&D organizations couldn't be further removed. "It's about the data," argues Dr. Amy Abernethy, Principal Deputy Commissioner of the FDA and experienced health data wrangler (2017 photo). Novartis CEO Vas Narasimhan candidly alluded to this in January when he reflected on his company's digital transformation journey, and said, "The first thing we've learned is the importance of having outstanding data to actually base your ML on. In our own shop, we've been working on a few big projects, and we've had to spend most of the time just cleaning the data sets before you can even run the algorithm. That's taken us years just to clean the datasets. I think people underestimate how little clean data there is out there, and how hard it is to clean and link the data."

Need more convincing that it will soon be impossible to tell whether a video of a person is real or fake? Enter Samsung's new research, in which a neural network can turn a still image into a disturbingly convincing video. Researchers at the Samsung AI center in Moscow have achieved this, Motherboard reported Thursday, by training a "deep convolutional network" on a large number of videos showing talking heads, allowing it to identify certain facial features, and then using that knowledge to animate an image. The results, presented in a paper called "Few-Shot Adversarial Learning of Realistic Neural Talking Head Models," are not as good as some of the deepfake videos you've seen, but to create those, you need a large number of images of the person you're trying to animate. The advantage of Samsung's approach is that you can turn a single still image (though the fidelity of the resulting video increases with more images) into a video.

Alexa's poor reputation for privacy may soon worsen as a patent filed by the firm suggests the virtual assistant may start listening before its'wake word' is said. Under the plans Alexa will be able to detect when it is being given a command even if the wake word is said at the end of the sentence instead of at the front. The move raises concerns over user privacy as Alexa will, by default, always be listening to conversations on the off-chance its wakeword is spoken. Alexa's poor reputation for privacy may soon worsen as a patent filed by the firm suggests the virtual assistant may start listening before its'wake word' is said. The patent, filed with the US Patent and Trademark Office, reveals the Seattle-fimrs plans for the next evolutionary step for it Alexa's technology.

The future of deliveries may be "robovans." A Chinese startup called Neolix kicked off mass production of its self-driving delivery vehicles Friday -- saying it's the first company globally to do so -- and has lined up giants such as JD.com Inc. and Huawei Technologies Co. as customers. Neolix expects to deliver a thousand of the vehicles, which resemble tiny vans, within the first year as it broadens out. The implications are potentially huge: Billionaire Jack Ma predicts there will be 1 billion deliveries a day in China within a decade and the commercialization of the technology could provide lessons for autonomous vehicles carrying passengers. Neolix isn't alone in this space as Silicon Valley's Nuro raised almost $1 billion this year and is starting to deliver groceries in Arizona.

Investment banking is seeing its historical profit centers eroded by technology and regulations. Core processes are being automated or commoditized. From IPOs, to M&A, to research and trading, investment banks are getting smaller, leaner, and scrambling to keep up with innovations. In 2006, investment banks were at the top of the finance world. With torrential growth and return on investment (ROI) driven largely by the trading of complex financial instruments, Lehman Brothers, Bear Stearns, Goldman Sachs and others achieved record profits and awarded unprecedented bonuses. Over the next two years, everything fell apart. Download the free report to learn how core processes of this financial service are being automated or commoditized. After the collapse of Lehman and Bear Stearns and the global financial crisis that ensued, the business models of the world's biggest investment banks needed to change. In the US, legislation emerged to forbid investment banks from prop trading, or trading with their own capital, and forcing them to keep more capital on hand. This regulation reduced trading profits and created a need to cut costs, spurring investment banks to spin off unprofitable divisions or eliminate them entirely. While the rules against prop trading have more recently been loosened, the restriction has still changed how investment banks operate. Moreover, as more and more companies raise large equity rounds they're also choosing to delay public offerings. And even when major tech companies do decide to go public, some, like Spotify and Slack, are doing so mostly without the help of banks. As a result, banks are facing dropping IPO profits: they generated just $7.3B in revenue in 2017 from equity capital markets, which includes IPOs, down an inflation-adjusted 43% since 2000's peak, according to the Wall Street Journal. At the same time, financial upstarts have built technologies that could eventually cut into the relationship-driven work that investment banks are used to doing. Instead of working with a bank to make an acquisition, you can use Axial -- the so-called "Tinder of M&A," for its algorithm-based approach to matching companies with potential buyers. In 2015, 26% of $1B mergers and acquisitions took place without the help of external financial advisors, up 13% from the year before, according to Dealogic.