QuantrolOx, a new startup that was spun out of Oxford University last year, wants to use machine learning to control qubits inside of quantum computers. The company, which was co-founded by Oxford professor Andrew Briggs, tech entrepreneur Vishal Chatrath, the company's chief scientist Natalia Ares and head of quantum technologies Dominic Lennon, today announced that it has raised a £1.4 million (or about $1.9 million) seed funding round led by Nielsen Ventures and Hoxton Ventures. Voima Ventures, Remus Capital, Dr. Hermann Hauser and Laurent Caraffa also invested in the round. The company's technology is technology-agnostic, and could be applied to all of the standard quantum computing technologies. The idea here is that instead of going through a slow manual tuning process, QuantrolOx's system will be able to tune, stabilize and optimize qubits significantly faster.

QuantrolOx, a new startup that was spun out of Oxford University last year, wants to use machine learning to control qubits inside of quantum computers. The company, which was co-founded by Oxford professor Andrew Briggs, tech entrepreneur Vishal Chatrath, the company's chief scientist Natalia Ares and head of quantum technologies Dominic Lennon, today announced that it has raised a £1.4 million (or about $1.9 million) seed funding round led by Nielsen Ventures and Hoxton Ventures. Voima Ventures, Remus Capital, Dr. Hermann Hauser and Laurent Caraffa also invested in the round. The company's technology is technology-agnostic, and could be applied to all of the standard quantum computing technologies. The idea here is that instead of going through a slow manual tuning process, QuantrolOx's system will be able to tune, stabilize and optimize qubits significantly faster.

FinnAir, an airline that dominates domestic and international air traffic in Finland, thought it could use AI to manage airport congestion. AI alone was not up to the job so Finland's largest airline instead implemented a hybrid system that uses AI to make predictions about air traffic and allows the humans-in-the-loop to make better decisions, explains Tero Ojanpera, CEO of Silo.ai, a Finnish AI lab that specializes in bringing cutting-edge AI talent to corporations around the world. Getting the FinnAir project to that point was not a question of plug and play. It required a complex multi-step modeling process to help the organization become more AI literate. Finnair's experience neatly illustrates the current state of play. AI is not fully ready to make the kind of decision-making corporates expect it to make and even if it were corporate teams and networks are not fully ready to implement and reap the full benefits of AI.

Most people find it a pain to receive parcels in wide time slots like, say, between 8 a.m. and 5 p.m., so when delivery startup Paack offered a service in which everyone could narrow that window down to one hour, with no extra charge, it had a challenge on its hands. The startup's routing engine worked but needed to be more efficient. Enter Prowler.io, a Cambridge, U.K.-based machine-learning startup that bills itself as a decision-making platform for any company with complex problems to solve. Paack's contact at venture firm Balderton in London introduced it to Prowler in February 2018, and within months its delivery vans and trucks were being coordinated by an intelligent, digital simulation. With the beta test over, Paack's CEO, Fernando Benito, sees a potential benefit to his bottom line. Some of his startup's deliveries are now 15% more efficient, he tells Forbes.

Everyone's had that coworker, the one who never asks for help even when fully out of their depth, unaware of their own incompetence. But what happens when your colleague isn't a human suffering from Dunning-Kruger but artificial intelligence? That's a question Vishal Chatrath has had to consider as the CEO and co-founder of Prowler.io, an AI platform for generalised decision making for businesses that aims to augment human work with machine learning. "The decision-making process can be quite similar [across different businesses], if abstracted at a low-enough level," he says. "In some cases, the decisions are fully automated, in some cases, there's a human in the loop. Keeping a human as part of the process is partially because of a lack of trust in machine-based decision making, but it's also an admission by Chatrath that we remain in the early years of AI. Such systems aren't perfect, and likely never will be, and one failing of AI is it doesn't inherently understand its own competency. If a human worker needs help, they can ask for it -- but how do you build an understanding of personal limitations into code? "In both crashes, the commonality was that the autopilot did not understand its own incompetence," Chatrath says. Prowler.io built an awareness of incompetence into its system, teaching its AI to not only understand its limitations but to forecast when it's going to reach a situation where it has no experience or background. "Then it gently taps the human on the shoulder, so to speak, for the human to take control," he says. The system can learn from those interactions, and after enough training may eventually be able to stop asking for help. Such limits to AI could be placed by regulators, as is the case in the financial industry where levels of risk are carefully weighed, or by the business itself. The fourth consideration is how are we even sure the AI is asking the right questions. "There is no cookie cutter answer to these," he says. If there's a 10 per cent chance a logistics scheduler is wrong, and a lorry is therefore a bit late, that's okay. If there's a 10 per cent chance that shape in front of a driverless car is a human, the car should stop -- the risk are too high for any uncertainty. "Rather than doing stupid things like running someone over, it brings the human into the [process]," Chatrath explains, as it's been told when the risks are too high for it to screw up. That's important, says Taha Yasseri, a researcher at the Oxford Internet Institute and the Alan Turing Institute for Data Science, because while we can delegate decision making to machines, we can't delegate responsibility. "The ultimate responsibility in implementing the decisions made by machines are on us," he says. In practice, whenever the expected accuracy of a human is higher than a machine, it is practically justified to use human judgment to overlook machine decisions."

Most people find it a pain to receive parcels in wide time slots like, say, between 8 a.m. and 5 p.m., so when delivery startup Paack offered a service in which everyone could narrow that window down to one hour, with no extra charge, it had a challenge on its hands. The startup's routing engine worked but needed to be more efficient. Enter Prowler.io, a Cambridge, U.K.-based machine-learning startup that bills itself as a decision-making platform for any company with complex problems to solve. Paack's contact at venture firm Balderton in London introduced it to Prowler in February 2018, and within months its delivery vans and trucks were being coordinated by an intelligent, digital simulation. With the beta test over, Paack's CEO, Fernando Benito, sees a potential benefit to his bottom line. Some of his startup's deliveries are now 15% more efficient, he tells Forbes.

Most people find it a pain to receive parcels in wide time slots like, say, between 8 a.m. and 5 p.m., so when delivery startup Paack offered a service in which everyone could narrow that window down to one hour, with no extra charge, it had a challenge on its hands. The startup's routing engine worked but needed to be more efficient. Enter Prowler.io, a Cambridge, U.K.-based machine-learning startup that bills itself as a decision-making platform for any company with complex problems to solve. Paack's investors at Balderton in London introduced it to Prowler in February 2018, and within months its delivery vans and trucks were being coordinated by an intelligent, digital simulation. With the beta test over, Paack's CEO, Fernando Benito, sees a potential benefit to his bottom line. Some of his startup's deliveries are now 15% more efficient, he tells Forbes.

Most people find it a pain to receive parcels between wide time slots like 8am and 5pm, so when delivery startup Paack offered a service where everyone could narrow that window down to one hour, with no extra charge, it had a challenge on its hands. The startup's routing engine worked but needed to be more efficient. Enter Prowler.io, a Cambridge, UK-based machine-learning startup that bills itself as a decision-making platform for any company with complex problems to solve. Paack's investor at Balderton in London introduced it to Prowler in February 2018 and within months, its delivery vans and trucks were being coordinated by an intelligent, digital simulation. With the beta test over, Paack's CEO Fernando Benito sees a potential benefit to his bottom line. Some of his startup's deliveries are now 15% more efficient, he tells Forbes.

Cambridge AI decision making platform, PROWLER.io, will be centre stage in California in May as the award-winning startup holds a provocative thought leaders' summit. Business Weekly's newly crowned Startup of the Year is bringing together a cohort of great minds to push the frontiers of AI thinking for a one-day event in Palo Alto on May 9. Founder and CEO Vishal Chatrath says it will be the first of many such think tanks talking about "AI taking decisions – leaving today's discussions about perception and classification in our wake." Chaired by David Rowan, editor-at-large of WIRED magazine, the event is designed, in Chatrath's words, "to share bold provocations on the future of AI." Guests will be drawn from academia, big tech, government, complexity theory, finance, gaming, quantum, safety tech and regulation. Speakers will give a 15 minute talk, ending with "a bold provocation around decision making and AI. "We are deliberately curating a wide-ranging agenda for the first of an annual event series for PROWLER.io," said Chatrath.

As we continue to see a wide proliferation of artificial intelligence-based startups come to market, one of the persistent and big questions has been is whether an AI system will ever be able to make decisions as well as a human can. A startup out of Cambridge called Prowler.io is developing a new kind of decision-making platform based on probabilistic modelling, reinforcement learning and game theory that it believes may help the AI community answer that question with a "yes." Co-founded by two alums from another AI company, VocalIQ, which was acquired by Apple 13 months after launch -- Prowler.io today is announcing that it has raised £10 million ($13 million) to help it along the way. Led by new investor Cambridge Innovation Capital, the round also had participation from Atlantic Bridge Capital as well as previous investors Passion Capital, Amadeus Capital Partners and SG Innovate, who participated in Prowler's $2 million seed round last year. Artificial intelligence has become an increasingly crowded area.