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Staff Machine Learning Engineer, Computational Finance

#artificialintelligence

At Affirm, People Come First is one of our core values, and that's why diversity and inclusion are vital to our priorities as an equal opportunity employer. You can read about our D&I program here and our progress thus far in our 2020 DEI Report. We also believe It's On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process. We will consider for employment qualified applicants with arrest and conviction records in accordance with applicable federal, state, and local laws, including the San Francisco Fair Chance Ordinance.


Optimizely updates its Full Stack platform with new data tools, enterprise integrations

ZDNet

San Francisco-based web experimentation company Optimizely is releasing a new version of its flagship platform that includes a new user interface, new data and analytics offerings, and integrations with AWS and Salesforce. Optimizely's core product is Web Experimentation, which enables non-technical staff to conduct A/B testing on the company's website using Optimizely's visual editor. Meantime, Optimizely's Full Stack product enables developers to experiment deeper into the tech stack to test things like search ranking algorithms or mobile app functionality. A/B testing has been a notable space of the software market as customers look to develop digital channels and improve experiences. Optimizely allows for quick A/B testing that can speed up software and code delivery.


15 jobs no one knew about in 2010 that everyone will want in 2020

#artificialintelligence

LinkedIn released its list of the top emerging jobs for 2020. These jobs have grown substantially in the last five years, and LinkedIn predicts they will continue to increase demand in the new year. Demand for artificial intelligence specialists grew 74% over the last five years. The job requires fluency in deep learning and machine learning. Cities hiring the most for artificial intelligence specialists include Boston and San Francisco.


Nightfall raises $20.3 million for AI that prevents sensitive data leaks

#artificialintelligence

Nightfall (formerly Watchtower AI), a San Francisco-based provider of cloud data loss prevention solutions, today emerged from stealth with $20.3 million in funding led by Bain Capital Ventures and Venrock, with participation from Pear VC and Atlassian CTO Sri Viswanath. CEO Isaac Madan said the proceeds from this latest round will bolster Nightfall's R&D and market expansion. "Our mission at Nightfall is to build the control plane for cloud data, enabling enterprises to know what data they have across the cloud, and to proactively manage and protect that information," said Madan, who was previously with Venrock's investment division. Nightfall's eponymous platform monitors data flowing into and out of the services a customer uses, which machine learning algorithms classify as sensitive, personally identifiable (PII), noncompliant (with regulations like HIPAA and GDPR), or safe to share. Using a visual dashboard, admins can set up automated workflows for quarantines, deletions, alerts, and more that integrate with dozens of software-as-a-service (SaaS) platforms and APIs, and view analytics metrics like real-time and historical PII count by type.


Investor Jocelyn Goldfein to join us on AI panel at TechCrunch Sessions: Enterprise – TechCrunch

#artificialintelligence

Artificial intelligence is quickly becoming a foundational technology for enterprise software development and startups have begun addressing a variety of issues around using AI to make software and processes much more efficient. To that end, we are delighted to announce that Jocelyn Goldfein, a Managing Director at Zetta Venture Partners will be joining on us a panel to discuss AI in the enterprise. It will take place at the TechCrunch Sessions: Enterprise show on September 5 at the Yerba Buena Center in San Francisco. It's not just startups that are involved in AI in the enterprise. Some of the biggest names in enterprise software including Salesforce Einstein, Adobe Sensei and IBM Watson have been addressing the need for AI to help solve the enterprise data glut.


VMware and Nvidia partner to simplify virtualised GPUs

#artificialintelligence

Nvidia announced its new enterprise software product, vComputeServer, which has been developed and optimised for use with VMware's vSphere. Last week, VMware announced its intention to acquire Carbon Black and Pivotal, in a massive deal that will expand the company's SaaS offerings, while enhancing its ability to enable digital transformation for customers. Before the dust had even settled on that news, the company announced today (26 August), that it is set to launch a hybrid cloud on AWS (Amazon Web Services) in partnership with Nvidia, which will improve GPU (graphics processing unit) virtualisation. The two companies say that this is the first hybrid cloud service that lets enterprises accelerate AI, machine learning or deep learning workloads with GPUs. At the VMWorld conference in San Francisco, Nvidia's VP of product management, John Fanelli, told reporters: "In a modern data centre, organisations are going to be using GPUs to power AI, deep learning and analytics. "Due to the scale of those types of workloads, they're going to be doing some processing on premise in data centres, some processing in clouds and continually iterating between them." The company said that this will make the completion of deep learning training up to 50 times faster than with a CPU alone. This product is aimed at people who may be using Nvidia's Rapids software, Fanelli explained, which is a suite of data processing and machine learning libraries used for GPU-acceleration in data science workflows. Nvidia founder and CEO Jensen Huang said: "From operational intelligence to artificial intelligence, businesses rely on GPU-accelerated computing to make fast, accurate predictions that directly impact their bottom line.


Nvidia, VMware to Bring Virtual GPUs to VMware's AWS Cloud

#artificialintelligence

If you've ever found yourself wishing you could do all the things you've been able to do with a hypervisor and regular virtual machines but on a GPU cluster – in your own data center or in the cloud – Nvidia and VMware are now saying your wish is about to come true. Monday morning, in conjunction with the start of VMworld in San Francisco, the two companies announced that VMware Cloud on AWS, the VMware-operated cloud service running on bare-metal infrastructure in AWS data centers, will soon feature virtualized GPUs you'll be able to provision and manage using the same vSphere tools you use with regular VM infrastructure. You'll be able to share a single physical GPU among multiple VMs, but you'll also be able to aggregate the power of many GPUs to train a machine-learning model at massive scale, the companies said. Related: VMworld: Look at Acquisitions for Virtualization's Cloud Play The play here is to get VMware into the infrastructure mix for the emerging set of enterprise computing workloads that benefit from GPU acceleration, such as AI and machine learning, as well as more traditional Big Data analytics. Also on Monday, the company announced a broad strategy for tackling the hybrid cloud opportunity, which is essentially to provide a single set of tools for managing all enterprise infrastructure, on premises and/or in any public cloud, in a uniform way.


VMware and Nvidia launch hybrid cloud on AWS for machine learning

#artificialintelligence

Nvidia and VMware today announced an enterprise-grade hybrid cloud on AWS that is optimized for machine learning, AI, and data science workflows. The VMware Cloud on AWS with Nvidia is capable of operating from cloud and on-premise servers and will make it easier to migrate VMware vSphere-based applications to the cloud to accelerate high-performance computing or machine learning for research, experimentation, and deployment in production. Today's news comes at the beginning of the VMworld conference in San Francisco and just days after VMware acquired cloud security and app development startups Pivotal and Carbon Black for $5 billion. Nvidia today also introduced vCompute Server for the GPU-accelerated deployment of workloads in virtual environments, including VMware's vSphere, vCenter, and VMware Cloud. The latest virtual GPU offering from Nvidia can make the completion of deep learning training up to 50 times faster than with a CPU alone.


Sales Enablement tools powered by Machine Learning and AI Artificial intelligence

#artificialintelligence

After a decade of Sales Enablement vendors having to optimize their experiences for mobile, now almost every new vendor seems to have a Machine Learning (ML) or Artificial Intelligence (AI) story to tell. Here my list of Sales Enablement tools powered by – or at least integrating – ML / AI (obviously most uses of the term Artificial Intelligence are talking about Machine Learning). Sales Enablement: Transform your sales strategy with impactful sales enablement applications to sell more. "Sales teams rely on our AI-powered WinScores, Opportunity Insights and Opportunity Maps to take control of pipeline and deliver better, more predictable outcomes." Aviso's AI-powered platform for sales helps close more deals. The company's mobile, AI-powered sales enablement automation platform's user experience empowers reps to more effectively engage with customers & prospects & encourages team-wide adoption. Customers include AT&T, ThermoFisher, Merck, ANZ Bank.


What a program for The IT Press Tour #28

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The IT Press Tour, the leading IT event for IT press, has unveiled a few days ago participating companies for the 28th edition scheduled mid-October in San Francisco. Nine companies will joins us with 7 new and 2 who come back respectively for the second time for Platfom.sh and third time for Sysdig. All seven others are new participants, here is the full list: Aera Technology, AI/ML for enterprise management, H2O.ai, open source data science and machine learning platform, Kinetica, GPU database, LogicMonitor, SaaS-based performance monitoring, Mabl, ML-driven test automotion service, Odaseva, Salesforce data management and GDPR, Platform.sh, The week will be dense with hot topics and great speakers and leaders, the tour will rock again. I invite you to follow us with @ITPressTour, #ITPT, various publications and reporters Twitter handles.