Microsoft is experiencing a major outage, so that’s why you can’t get any work done.
Besides its homepage, Microsoft services are down, log-in pages aren’t loading, and even the company’s status pages were kaput. Worse, Microsoft’s cloud service Azure appeared to also be offline, causing outages to any sites and services that rely on it.
It’s looking like a networking issue, according to the status page — when it loaded. Microsoft also tweeted that it was related to DNS, the internet system that translates web addresses to computer-readable internet numbers. It’s an important function …
Google Cloud today announced a new operating mode for its Kubernetes Engine (GKE) that turns over the management of much of the day-to-day operations of a container cluster to Google’s own engineers and automated tools. With Autopilot, as the new mode is called, Google manages all of the Day 2 operations of managing these clusters and their nodes, all while implementing best practices for operating and securing them.
This new mode augments the existing GKE experience, which already managed most of the infrastructure of standing up a cluster. This ‘standard’ experience, as Google Cloud now calls it, is still available …
OAKLAND, Calif. — When Jeff Barr, a prominent executive at Amazon’s cloud computing division and a prodigious corporate blogger, celebrated his 60th birthday last year, Corey Quinn had a surprise for him: a music video that mocked Amazon’s business.“Jeff, can you write me a launch blog post,” sang a cartoon Amazon manager to the tune of Billy Joel’s “Piano Man.” “What we’ve built is a mystery to me. But it’s vast and bespoke and its console’s a joke. But if it ships, I might make V.P.”After the video’s release, Mr. Quinn, …
SEATTLE — In 2002, Andy Jassy, a young executive at Amazon, began closely shadowing Jeff Bezos, the founder of the online bookstore.Mr. Jassy followed Mr. Bezos everywhere, including board meetings, and sat in on his phone calls, said Ann Hiatt, who was Mr. Bezos’ executive assistant from 2002 to 2005. The idea, she said, was for Mr. Jassy to be “a brain double” for Mr. Bezos so that he could challenge his boss’s thinking and anticipate his questions.“I thought that I had very high standards before I started that job,” Mr. Jassy said in a podcast interview last fall about the 18 …
It’s been a busy year of expansion for the large cloud providers, with AWS, Azure and Google aggressively expanding their data center presence around the world. To cap off the year, Google Cloud today announced a new set of cloud regions, which will go live in the coming months and years. These new regions, which will all have three availability zones, will be in Chile, Germany and Saudi Arabia. That’s on top of the regions in Indonesia, South Korea, the U.S. (Last Vegas and Salt Lake City) that went live this year — and the upcoming regions in …
Back in 2018, Google announced that it would provide $9 million in Google Cloud Platform credits — divided over three years — to the Cloud Native Computing Foundation (CNCF) to help it run the development and distribution infrastructure for the Kubernetes project. Previously, Google owned and managed those resources for the community. Today, the two organizations announced that Google is adding on to this grant with another $3 million annual donation to the CNCF to “help ensure the long-term health, quality and stability of Kubernetes and its ecosystem.”
As Google notes, the funds will go to the testing and infrastructure of the Kubernetes project, which …
As the Chinese government tracked and persecuted members of predominantly Muslim minority groups, the technology giant Alibaba taught its corporate customers how they could play a part.Alibaba’s website for its cloud computing business showed how clients could use its software to detect the faces of Uighurs and other ethnic minorities within images and videos, according to pages on the site that were discovered by the surveillance industry publication IPVM and shared with The New York Times. The feature was built into Alibaba software that helps web platforms monitor digital content for material related to terrorism, pornography and other …
Eric Tan is Senior Vice President of IT and Business Services Coupa, a leader in business spend management and a former Battery portfolio company.
Ever since the pandemic hit the U.S. in full force last March, the B2B tech community keeps asking the same questions: Are businesses spending more on technology? What’s the money getting spent on? Is the sales cycle faster? What trends will likely carry into 2021?
Recently we decided to join forces to answer these questions. We analyzed data from the just-released Q4 2020 Outlook of the Coupa Business Spend …
AI startup RealityEngines.AI changed its name to Abacus.AI in July. At the same time, it announced a $13 million Series A round. Today, only a few months later, it is not changing its name again, but it is announcing a $22 million Series B round, led by Coatue, with Decibel Ventures and Index Partners participating as well. With this, the company, which was co-founded by former AWS and Google exec Bindu Reddy, has now raised a total of $40.3 million.
In addition to the new funding, Abacus.AI is also launching a new product today, which it calls Abacus.AI Deconstructed. Originally, the idea behind RealityEngines/Abacus.AI was to provide its users with a platform that would simplify building AI models by using AI to automatically train and optimize them. That hasn’t changed, but as it turns out, a lot of (potential) customers had already invested into their own workflows for building and training deep learning models but were looking for help in putting them into production and managing them throughout their lifecycle.
“One of the big pain points [businesses] had was, ‘look, I have data scientists and I have my models that I’ve built in-house. My data scientists have built them on laptops, but I don’t know how to push them to production. I don’t know how to maintain and keep models in production.’ I think pretty much every startup now is thinking of that problem,” Reddy said.
Image Credits: Abacus.AI
Since Abacus.AI had already built those tools anyway, the company decided to now also break its service down into three parts that users can adapt without relying on the full platform. That means you can now bring your model to the service and have the company host and monitor the model for you, for example. The service will manage the model in production and, for example, monitor for model drift.
Another area Abacus.AI has long focused on is model explainability and de-biasing, so it’s making that available as a module as well, as well as its real-time machine learning feature store that helps organizations create, store and share their machine learning features and deploy them into production.
As for the funding, Reddy tells me the company didn’t really have to raise a new round at this point. After the company announced its first round earlier this year, there was quite a lot of interest from others to also invest. “So we decided that we may as well raise the next round because we were seeing adoption, we felt we were ready product-wise. But we didn’t have a large enough sales team. And raising a little early made sense to build up the sales team,” she said.
Reddy also stressed that unlike some of the company’s competitors, Abacus.AI is trying to build a full-stack self-service solution that can essentially compete with the offerings of the big cloud vendors. That — and the engineering talent to build it — doesn’t come cheap.
Image Credits: Abacus.AI
It’s no surprise then that Abacus.AI plans to use the new funding to increase its R&D team, but it will also increase its go-to-market team from two to ten in the coming months. While the company is betting on a self-service model — and is seeing good traction with small- and medium-sized companies — you still need a sales team to work with large enterprises.
Come January, the company also plans to launch support for more languages and more machine vision use cases.
“We are proud to be leading the Series B investment in Abacus.AI, because we think that Abacus.AI’s unique cloud service now makes state-of-the-art AI easily accessible for organizations of all sizes, including start-ups,” Yanda Erlich, a p artner at Coatue Ventures told me. “Abacus.AI’s end-to-end autonomous AI service powered by their Neural Architecture Search invention helps organizations with no ML expertise easily deploy deep learning systems in production.”
Seldon is a U.K. startup that specializes in the rarified world of development tools to optimize machine learning. What does this mean? Well, dear reader, it means that the “AI” that companies are so fond of trumpeting does actually end up working.
It has now raised a £7.1 million Series A round co-led by AlbionVC and Cambridge Innovation Capital . The round also includes significant participation from existing investors Amadeus Capital Partners and Global Brain, with follow-on investment from other existing shareholders. The £7.1 million funding will be used to accelerate R&D and drive commercial expansion, take Seldon Deploy — a new enterprise solution — to market and double the size of the team over the next 18 months.
More accurately, Seldon is a cloud-agnostic machine learning (ML) deployment specialist which works in partnership with industry leaders such as Google, Red Hat, IBM and Amazon Web Services.
Key to its success is that its open-source project Seldon Core has more than 700,000 models deployed to date, drastically reducing friction for users deploying ML models. The startup says its customers are getting productivity gains of as much as 92% as a result of utilizing Seldon’s product portfolio.
Alex Housley, CEO and founder of Seldon speaking to TechCrunch explained that companies are using machine learning across thousands of use cases today, “but the model actually only generates real value when it’s actually running inside a real-world application.”
“So what we’ve seen emerge over these last few years are companies that specialize in specific parts of the machine learning pipeline, such as training version control features. And in our case we’re focusing on deployment. So what this means is that organizations can now build a fully bespoke AI platform that suits their needs, so they can gain a competitive advantage,” he said.
In addition, he said Seldon’s open-source model means that companies are not locked-in: “They want to avoid locking as well they want to use tools from various different vendors. So this kind of intersection between machine learning, DevOps and cloud-native tooling is really accelerating a lot of innovation across enterprise and also within startups and growth-stage companies.”
Nadine Torbey, an investor at AlbionVC, added: “Seldon is at the forefront of the next wave of tech innovation, and the leadership team are true visionaries. Seldon has been able to build an impressive open-source community and add immediate productivity value to some of the world’s leading companies.”
Vin Lingathoti, partner at Cambridge Innovation Capital, said: “Machine learning has rapidly shifted from a nice-to-have to a must-have for enterprises across all industries. Seldon’s open-source platform operationalizes ML model development and accelerates the time-to-market by eliminating the pain points involved in developing, deploying and monitoring machine learning models at scale.”