Mel Brooks and Carl Reiner used to spend every evening watching movies. Their favourites were cheesy – the type of film where someone says, "Secure the perimeter!" Why do I mention this in the context of Foundation? Because this adaptation of Isaac Asimov's novels started out as a thought-provoking series, but is now a "Secure the perimeter!" It has been two years since Foundation last aired, so if you have forgotten where we left off, that is understandable.

Seldon, a London-based data-centric machine learning operations (MLOps) platform, has secured a $20M Series B funding round led by new Portuguese investor Bright Pixel (former Sonae IM) with participation from existing investors AlbionVC (backed Ophelos), Cambridge Innovation Capital, and Amadeus Capital Partners. The funding will help Seldon expand its machine learning product's market fit and unlock enterprise-ready solutions based on open source. "AI is in everything, and Seldon is uniquely positioned to ensure a return on ML investment by providing robust, scalable, and secure infrastructure, pioneering a data-centric approach to ML pipelines, prioritizing team collaboration across the organization, and making sure teams can solve meaningful problems at scale by building trust in machine learning, even under the most intense regulatory conditions. "We're excited to bring together new investor Bright Pixel Capital and our existing partners, who believe in our vision and can help us become the trusted MLOps partner of any organization worldwide." Currently, numerous companies are investing a lot of resources into artificial intelligence, but they are having difficulty expanding their models for practical use. This is due to bottlenecks in team workflows, increased regulation and compliance restraints, a lack of trust in model outputs, and ensuring peak model performance are all top of mind for AI-powered enterprises. Here's where Seldon helps Data Scientists, ML Engineers, and other stakeholders in the company to quickly and efficiently adopt machine learning to address these challenges. Founded in 2014, Seldon is a data science and machine learning operations platform that aims to empower Data Scientists, ML Engineers, and MLOps teams to deploy, monitor, explain, and manage their ML models. With Seldon, organisations can minimise risk and drastically cut down time-to-value from their models. The UK company offers both an open-source framework, "Core," which focuses on model deployment, and an enterprise product, "Deploy Advanced," which builds on this functionality to power model monitoring, explainability, and management. Seldon claims that it has achieved a 400% YoY growth rate in its open-source frameworks installed and running since its series A in November 2020. "Seldon has differentiated itself by presenting a unique solution that can reduce the friction for users deploying and explaining ML models across any industry.

Seldon, a data-centric machine learning operations (MLOps) platform for the deployment, management, monitoring and explainability of machine learning (ML) models, announced a $20M Series B funding round today. The round was led by new investor Bright Pixel (former Sonae IM) with significant participation from existing investors AlbionVC, Cambridge Innovation Capital, and Amadeus Capital Partners. Organizations are investing heavily in AI but many are struggling to scale out their models in production due to bottlenecks in team workflows, increased regulation and compliance restraints, a lack of trust in model outputs, and ensuring peak model performance are all top of mind for AI-powered enterprises. Seldon empowers Data Scientists, ML Engineers and other business stakeholders to accelerate the adoption of machine learning to help solve these challenges with unprecedented efficiency. "AI is in everything, and Seldon is uniquely positioned to ensure a return on ML investment by providing robust, scalable and secure infrastructure, pioneering a data-centric approach to ML pipelines, prioritizing team collaboration across the organization and making sure teams are able to solve meaningful problems at scale by building trust in machine learning, even under the most intense regulatory conditions. "We're excited to bring together new investor Bright Pixel Capital and our existing partners, who believe in our vision and can help us become the trusted MLOps partner of any organization worldwide." As a category leader in the MLOps space, the funding will be used to continue to pioneer a data-centric approach to AI across Seldon's suite of products. Seldon has achieved a remarkable 400% YoY growth rate in its open source frameworks installed and running since its series A in November 2020. Seldon's cutting-edge research, in collaboration with teams at Cambridge University, has been key to their innovative product development and is a central focus of the company following the raise. Seldon is also investing in customer success and strengthening the global support function. "Seldon has differentiated itself by presenting a unique solution that is able to reduce the friction for users deploying and explaining ML models across any industry.

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Machine Learning Engineer at Seldon United Kingdom › London (Posted Jan 8 2022) Job description London OR Cambridge, UK (hybrid) Seldon is looking for talented Software Engineers with Machine Learning expertise to join our growing Engineering team. This role covers various positions in the software engineering team including backend product, open source MLOps and client facing machine learning engineers and can fit applicants from a range of seniority levels. We are focused on making it easy for machine learning models to be deployed and managed at scale in production. We provide Cloud Native products that run on top of Kubernetes and are open-core with several successful open source projects including Seldon Core, Alibi:Explain and Alibi:Detect. We also contribute to open source projects under the Kubeflow umbrella including KFServing.

An innocent viewer of the new Apple TV series "Foundation"--a lavish production complete with clone emperors, a haunted starship, and a killer android who tears off her own face--might be surprised to learn that the novels it's based on inspired Paul Krugman to become an economist. Isaac Asimov's classic saga revolves around the dismal science of "psychohistory," a hybrid of math and psychology that can predict the future. Its inventor, Hari Seldon, lives in a twelve-thousand-year-old galactic empire, which, his equations reveal, is about to collapse. "Interstellar wars will be endless," he warns. His followers establish a Foundation on the frontier world of Terminus--a colony tasked with conserving all human knowledge--where they spend the next millennium fulfilling "Seldon's plan" to reunite the galaxy.

Ahead of the show's Apple TV premiere on September 24th, Apple has offered another look at its latest sci-fi saga, Foundation. The latest trailer doesn't reveal too much about the story, but it has some impressive visuals. The clip features a elevator that, according to showrunner David S. Goyer, stretches around 26 miles into space. There's also a floating visualization of a supercomputer that takes design cues from a Möbius strip. Goyer told IGN that he challenged his production team to find a look that didn't remind viewers of Star Wars or Star Trek, perhaps the two biggest linchpins of science fiction.

A London machine learning tech company has secured multi-million pound investment to grow its international footprint and bolster its research and development capabilities. Shoreditch-based Seldon has raised £7.1m in a Series A funding round in order to develop new offices in both the UK, the US and Asia. Founded in 2014, Seldon specialises in cloud agnostic machine learning deployment, and works in partnership with brands such as Google, Red Hat, IBM and Amazon Web Services. The firm's suite of products aims to enhance machine learning deployment pipelines with explainability, governance and monitoring functions. Co-led by AlbionVC and Cambridge Innovation Capital, the round also saw participation from existing investors Amadeus Capital Partners and Global Brain, with follow-on investment from other existing shareholders.

Science Fiction writing in itself is an exercise of modeling the future based on present and past culture. Therefore, integrating predictive algorithms in literature works has been an intuitive choice. Isaac Asimov was a prolific 20th century American writer and professor. He wrote or edited more than 500 books and is one of the most popular SF writers of all time. The Foundation Series is one of his most notable and comprehensive works.

As the age of AI approaches, the question of whether robots can replace teachers looms larger. Anthony Seldon, vice chancellor of the University of Buckingham, predicts that robots will replace teachers by 2027, less than a decade away. Some say that robots can never replace teachers because teachers inspire us. But, in another article, Seldon, says "inspirational robots" are possible and can be adapted to each student's individual learning style. The idea of robot teachers may sound appealing on some levels because teachers are expensive and in increasingly short supply.