“The NRC’s review of NuScale’s DCA began March 2017 and the NRC’s final report approving the design is expected to be complete by September 2020. Once approved, certified NuScale SMRs will be available to domestic customers to be licensed for construction and operation. NuScale Power is the only company to have submitted an SMR DCA. Regulatory approval will support its first U.S. deployment by the mid 2020’s, further establishing NuScale as the leader in SMR technology.” source: NuScale Newsroom, 9 Jan 2018.
The World Nuclear Association from London, UK, is lobbying for a 25% nuclear share in the global electricity market of 2050. It is an ambitious target that goes under the programme named Harmony , with three main areas to develop: a level playing field, harmonised regulatory processes, an effective safety paradigm.
The latest paper from Tokamak Energy Ltd, UK, titled “Compact fusion energy based on the spherical tokamak” is out. Their most relevant contribution is summarised as: “The small scale of the fusion modules should lead to rapid development and make possible the resolution of the remaining key outstanding physics and technology steps that are needed for the realisation of fusion power.”, which is interesting because the ITER tokamak in Cadarache, France, is much larger than that at 6.2m radius against less than 1.5m! Tokamak Energy Ltd also has an ambitious commercial goal: “This technology will form the basis for the commercial module that the company expects to deliver electricity into the grid by 2030.” As always with innovative nuclear, materials science will be the key. Having a look soon.
It is more than one year I am following recommender systems for websites deployment and I am now ready to bite. Another book from Manning, authored by Kim Falk and called Practical Recommender Systems , is going to be released in March but is out already as a complete pre-print! It uses the latest open source packages and puts all modules together for non-developers like me: front end, back end, machine learning & dev-op, output recommendations, market testing. That way, I can both work and learn from good up-to-date practices. Thanks!
I am too cynic for bandwagons, mining pools and speculation, so this is my humble advice: do your own research. If you do not understand the trading market fundamentals and the underlying raison d’etre of one cryptocurrency over another, just have a look at their market cap and treat them all as more or less expensive scratch cards. Even if you see the dynamics, just consider you are not smarter as well, this just being the latest Wild West instalment for 2018 chancers, criminals and fools. Call them pioneers and follow suit accordingly on BitcoinTalk.org forums.
Aha! A materials science competition in Kaggle called Novel Materials Discovery (NOMAD) Competition 2018: Predicting Key Properties of Novel Transparent Semiconductors. Why? “To avoid costly and inefficient trial-and-error of synthetic routes, computational data-driven methods can be used to guide the discovery of potentially more efficient materials to aid in the development of advanced (or totally new) technologies.” that’s right, even academies are now waking up to this, some startups working already. “Data-driven models offer an alternative approach to efficiently search for new possible compounds in targeted applications but at a significantly reduced computational cost.” Good, having a proper look and maybe competing, that’s exactly what I’m trying to do with materials for new nuclear plants. Thanks!
“Civilian nuclear facilities require thousands of digital systems to support their operation. Software patches and updates are even more challenging than routine maintenance, and tech support usually comes from a single vendor. Contrary to popular belief, a computer system that is isolated from unsecured networks (or “air-gapped”) is not immune to cyber attacks, which can come from a compromised supply chain or from insiders. The Stuxnet computer worm, for example, destroyed about 1,000 Iranian centrifuges between 2009 and 2010, despite the fact that critical systems were air-gapped. The worm spread to these systems from infected USB thumb drives.” — source: Bulletin of Atomic Scientists
E-book coming about the most critical issues in nuclear engineering for 2018, it will be short & clear with tons of internet references for own consultation. Previous instalments pulled off the Amazon shelves.
The DronesBench is now at the commercial stage and we are trying to penetrate the US market, which is currently estimated by the EASA at 4 million consumer drones sold (plus 1 million in Europe and 1 million in the South-East Asia). It will be difficult but interesting, a different approach for sure, more commercial than technological. I am still convinced the most likely outcome is a sort of acqui-hire by 2020, with Mauro Pompetti selling the project in full while becoming the lead technologist or a consultant for a bigger group. We will see in 2018, some legislation is expected worldwide and the numbers of the testing / certification business will become clear, in that moving (or not…) the giants.
Data scientists at commercial and startup scale cannot afford to know nothing about the operations going behind scene with machine learning subsystems. That’s where Jeff Smiths’ “Reactive Machine Learning Systems” latest book from Manning helps immensely. Just understanding the DevOps point of view would surely assist any practitioner to think of deployment better and “build machine learning applications that are responsive, resilient, and elastic.” In conclusion, “To make machine learning systems reactive, you need to understand both reactive design patterns and modern data architecture patterns.”