This episode we speak to Jose Carranza, a deep learning PhD researcher in Costa Rica who has taken his expertise to an unexpected field, that of the biological classification of plants.
This episode we speak to Elizabeth Iorns who is the Founder and CEO of Science Exchange. We wanted to get Elizabeth's view on what it really takes change the status quo in science - both from a process perspective in the way we conduct ourselves in a lab with regards to suppliers, but also from an activation standpoint - instead of training people up on reproducibility, actually going out and making change using the resources she had access to. We are all about finding role models for change at Science: Disrupt, and Elizabeth is a perfect example of someone who takes action and builds the future - making scientific revolution seem just that bit more achievable.
We speak to Chad Rigetti, CEO of quantum computing startup Rigetti Computing.
This episode we spoke to Imogen Bunyard, CoFounder of Qadre a startup focussed on building blockchain solutions that tackle trust issues within enterprises. This could include tackling the counterfeit drug market. Imogen has a particular knack for breaking down a complex topic (in this case the blockchain), grounding it reality, and imagining use cases that can really make a difference.
There's a lot of hype and plenty of misinformation around blockchain, it's either the domain of drug smugglers and the dark web; or like AI, it's presumed that it's a silver bullet for every company woe you can imagine. There's also little effort made to make the topic actually understandable, with convoluted analogies galore.
We were keen to hear about the paucity of academic research in the field as researchers are drawn away from the academy. There's plenty of articles on the idea of brain drain, as corporates look to build up their intellectual inventory by essentially buying up scientists (sometimes even entire labs). Research skills in data science, computer vision, or AI are incredibly lucrative propositions for organisations, and the big tech companies are hoovering up research departments left and right but at least those fields had time to become established as topics of study within most universities.
This episode was recorded in the bowels of Sussex University when we met up with Tom Baden a Neuroscientist interested in how the visual system processes information. Our motivation for chatting to Tom was a brilliant project called the FlyPi that he developed, along with Andre Chagas another Neuroscientist who joined us via the magic of Skype.
FlyPi is a great representation of a seemingly growing phenomena of DIY tools within the labs - you can read the paper for the specs, but in short it's a 3D printed lab for imaging experiments - specifically of the fruit fly (as the name FlyPi might suggest). Along with the FoldScope, and a number of other simple, cheap tools (including a fidget spinner centrifuge ...), the ability to probe the natural world in a meaningful way is being made available to a much wider audience.
We spoke a bunch about Tom's Trend in Africa programme, which trains up researchers in underserved parts of the continent so they're up to scratch with the latest neuroscience tools/knowhow. We also discussed the broad topic of the maker movement in biology, the fear of experimenting with experiments, and the way that DIY hardware in science needs to be shown off in the appropriate venues (and that means not just buried away in the academic literature).
We thoroughly enjoyed chatting to Andre and Tom, and we left feeling energised that the spirit of ingenuity, of tinkering, and playing with science is alive and well.
The showcase featuring 15 early stage biotech startups, was held in the swishy new Imperial College I-HUB.
This episode we speak to Zach Mueller, an Amazon Data Scientist and co-Founder of Sound.Bio, Seattle's first DIY Biohackspace. We wanted to hear about how they aim to build a community around biology, the challenges of setting up the lab, and the efforts they go to to educate Seattleites in modern biotech.
Zach comes to biology with little experience, in fact he was drawn to the field after listening to a podcast that spoke about IGEM, the synthetic biology competition for undergraduate teams. This idea of arriving at the lab with a minimal background in the science, is what these biohackspaces are all about. They're a place where you can experiment with experimenting, learn new skills, and join a community that is committed to producing value through biotech.
The space itself is kitted out with the kinds of tools you would expect in order to carry out modern biology experiments. However, the lab is also keen to leverage the skills and resourcefulness of the maker community, to really hammer home the important concept that biology doesn't have to be restricted to the confines of a university. Or perhaps more importantly, that participating in biology is not simply the reserve of institutions with pockets deep enough to purchase the latest tech.
In this episode we spoke to Jackie Hunter, CEO of Benevolent Bio, a company that utilises machine learning and AI to find previously overlooked drug candidates within the research literature. Jackie was previously Chief Executive of the BBSRC and comes into the AI space with a wealth of experience in industrial drug discovery.
How can we protect against the cyber threats of today and prepare for the threats of tomorrow? Darktrace are a rapidly growing tech company based out of San Francisco and Cambridge, UK who are getting well deserved attention with their novel approaches to both AI and cybersecurity. Founded through a collision of academic mathematicians and members of the security services who had been tackling state level attacks, Darktrace takes a very different approach to how cyber-attacks can be defended against. Speaking to Darktrace CMO Emily Orton, we got some insight into the challenges facing enterprises in todays interconnected world.
New advances in cyber-security are realistically legacy approaches whereby they rely on knowing who we’re protecting against and defending the perimeter from them. Orton highlighted that this approach is the same as building a moat around a Tuscan Castle: it’s not sufficient to protect us against modern techniques of infiltration. The issue today is that networks are too large and interconnected – there’s simply too many in-roads into a network for the ‘walled off’ style approach to be sustainable – as such, Darktrace are trying something different. The standard dogma of cybersecurity is that threats can be kept outside of the network. This has meant that the bulk of effort in the security sector and the IT industry at large, is based on the simplistic idea that we can just keep the bad guys out. However, this worldview historically hasn’t adjusted for defence against actors within the network itself.
Darktrace, while grounded in the heady mathematics of Machine Learning and Bayesian Probability Theory has taken inspiration from the Life Sciences. Specifically, in the way the Immune System operates. Our surface barrier, the skin, protects us from pathogens and foreign bodies. The ability to venture out into the world without fear of contracting an infection through simple contact is not something many are concerned about, and this is down to the efficacy of this barrier. However, the skin on its own is insufficient to produce a robust defence of the host – internal security mechanisms must be active. So, with this ‘bioinspiration’, Darktrace aims to catch anomalies from within the network, in what they term the ‘Enterprise Immune System’.
Machine Learning allows an enterprise to be alerted to unusual behaviour that would have previously gone unnoticed such as an insider syphoning off files, especially if that user isn’t already on some comprehensive watchlist. But Darktrace aren’t typically bumping up against malicious agents infiltrating some enterprise, interestingly much of their work in this context has to do with a technological naivety found in employees and their regard for basic data security. Orton pointed to a few groan-worthy examples of everyday behaviour that would stump security in the traditional paradigm: “We had a user sending massive files using iMessage because he couldn’t get them out. His company was so locked down. From what we could see he wasn’t malicious, he just wanted to get his work done. We’ve had game developers sending source code back on their Gmail accounts, these aren’t people that are trying to take the company down, again they’re just trying to do their work. Sometimes people just make mistakes, we’re seeing ransomware cases every week, and that’s always someone who clicked on links. And those phishing attacks are getting better and better”
There’s a general resignation in cybersecurity that as the creation of new threats occurs, awareness of those threats lags significantly. Orton noted that threats like polymorphic malware, are particularly problematic because they won’t appear in the security blogs until the malware has already undergone several ‘iterations’. The importance of automation now comes to the fore: action has to be taken in real time. The days of pushing software patches on the order of months after an infiltration are over.
It’s not simply in the defence of the network that Darktrace is applying their knowhow. Darktrace has proven to be an effective counter-puncher and bring to life the Immune System analogy with the company’s Antigena. This is an algorithm based counterstrike service that can intercept malicious actions before they can damage your core infrastructure and data. The cool thing about this is that, in essence, it’s the first time machine learning is responding to threats as opposed to just passive detection. As Orton intimated, “We now have a portion of our customers that love the machine learning so much, and have seen it in practice, that they trust that machine to take action on their behalf.” This highlights a larger point that there’s simply too many threats, and even with a 24/7 security team – there’s a capacity to what humans can deal with, and the volume of threats becomes an unmanageable problem when it comes to protecting your assets. She touched on the idea that automated cyber warfare is a likely reality, with automated hackers, tackling AI defence systems. But there’s an advantage to being on the defensive side, being proactive and assuming there will be attempts at infiltration: by learning everything you can about your network, you know the battlefield better than any attacker.
Machine Learning and Bayesian Stats are nothing new, so why has it taken so long for the likes of Darktrace to come along? Processing power certainly has a hand in that. But again, the scale of the networks and sheer difference between the network architecture of one enterprise to another makes this an unusual and previously intractable challenge: if you’re at a media agency, Facebook may be whitelisted; walk into a bank and these sites will be firmly on the blacklist. Additionally, you can include remote working and freelancing to the complexity.
In order to handle the variability in the threats, various algorithms are employed which are then filtered for performance. Darktrace are tracking many events, with automation allowing them to probe hundreds of metrics of behavior. These could include the login time stamps, volume of data transfer, and the frequency of data transfer. Perhaps a user logs into their computer at 2am, this may be unusual, but not something that would pass the threshold in order to be flagged to the security personnel. However, if they also see the connection was to somewhere in Ukraine, a pattern of behaviour not previously seen in the user history, and perhaps the volume of data being transferred far exceeded your typical usage, then that would be flagged. The enterprise itself makes the decision on how sensitive they are to these flags – a financial institution will have a lower threat tolerance than another for example.
All users, the devices they use, and the network as a whole are all modelled, and as such Darktrace are learning what’s normal for that user, that device, that network. However, this data set is not producing a static baseline of events, the system Darktrace is deploying is calculating probabilities based on evolving evidence.
After all, if the threats are constantly innovating, surely our defence should be too?
On May 16th, we brought the Future of Energy to the Royal Academy of Engineering with our fifth Science: Disrupt London Session. We covering a ton of ground, on the vast world of renewables, the complicated problem of energy storage, and how distributed energy systems could be the way forward in emerging markets.
We were joined by three brilliant speakers who shared their insight on the rapidly changing Energy space.
To kick off the night, though, we had a fab intro from Nick Winser CBE, Chair of the Energy Systems Catapult:
Our first speaker was Melissa Stark, a Managing Director in Accenture’s Energy industry group. Melissa's focus is on natural gas, LNG, and Renewable generation. With over 22 years of experience working across all sectors of the energy industry Melissa was able to clue our audience in on the efforts and work done in energy R&D, investment, decision support and supply chain.
Next we had, Angelo Prete Chairman of Teraloop, a Helsinki based kinetic energy storage company utilising large scale flywheel technology.
Check out Angelo's slides here.
Our third speaker was Elizabeth Nyeko the Co-Founder of Mandulis Energy. Launched in Uganda, Mandulis Energy develops software-enabled grid and off-grid renewable energy projects in emerging markets, including the supply of sustainable biomass to large-scale electricity producers.
Check out Elizabeth's slides here.
Finally we had Dr Stephen Hall of the University of Leeds. Stephen currently holds an EPSRC fellowship investigating deep decarbonisation of cities. He is interested in the links between low carbon innovation, economics, energy, climate change and society. In particular he is interested in the role of cities and regions in delivering infrastructures compatible with low carbon futures.
Check out Steve's slides here.
We capped the evening off with a panel and audience Q&A hosted by Nick Winsor. NIck was appointed Chairman of the Energy Systems Catapult in January 2015 and has been a Non Executive Director of Kier Group since 2009 where he also Chairs its Safety, Health and Environment Committee. Nick was also previously UK CEO and Board Member of National Grid.
HackScience are building open and financially accessible hardware tools to accelerate research.
This Thursday, we are venturing to Amsterdam for the 5th edition of the Thought For Food Summit - and looking at the plans for this extraordinary event, we are pretty excited..!
This week we chatted to Chris Hartgerink a PhD metascientist (the science of science) andopen access advocate, whose core focus is on data fraud.
This episode we spoke to Michael Eisen (@mbeisen), a Professor within the Molecular and Cellular Biology Department at the University California, Berkeley, founder of PLOS, and an aspiring Senator.