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C3.ai Expands Its Portfolio of AI-Powered As-a-Service Solutions With C3 Energy Management
C3.ai, a leading enterprise AI software provider (and a new venture by Tom Siebel of Siebel Systems), announced in October 2019 the launch of Smart Institutions, an AI-powered, holistic energy-as-a-service software solution for universities, municipalities, corporate campuses, and hospitals. This is a joint solution with ENGIE, a French multinational electric utility company.
Smart Institutions enables organizations to proactively and automatically manage their buildings and energy assets to increase sustainability, enhance energy efficiency, and decrease costs. It has been deployed at the Ohio State University Columbus campus with the goal to reduce energy use across its 485 buildings.
Smart Institutions is built on C3 Energy Management, an enterprise-scale SaaS that uses machine learning and advanced AI and optimization algorithms to model building operations, detect anomalies, predict opportunities for energy savings, and help facilities managers take action in near real time.
C3 Energy Management, in turn, is powered by the company’s C3 AI Suite platform for rapid development, deployment, and operationalization of large-scale AI applications.
Solutions such as Smart Institutions and C3 Energy Management should make it easier for organizations to reap the benefits of machine learning and AI without a heavy investment in resources and skillsets required to build, train, and operate machine learning models.
Google has access to personal medical data of up to 50 million Americans through its partner Ascension, the second-largest health network in the US. The information about “Project Nightingale” has come from a whistleblower, reports The Guardian.
Google has been accused of secretly collecting sensitive patient data in the US on behalf of the healthcare provider Ascension. While most of the criticism has been about data privacy, we should also consider what Google intends this data for.
Google continues to be an ally in the war against deepfake deception, releasing a large dataset of video deepfakes that it has produced with the intent of helping researchers detect visual deepfakes.
To make machine learning (ML) repeatable and scalable, you need to invest in serving infrastructure (the “last mile”), ML operations, and governance, says Cloudera’s Sr. Product Manager Alex Breshears in the MIT-Cloudera webinar “How to Scale Production Machine Learning in the Enterprise.”
Databricks, a data processing and analytics platform with a strong focus on artificial intelligence (AI) and machine learning (ML), is investing 100 million euros (US$111 million) in its European Development Center to take advantage of the European pool of talent and cutting-edge research.
KenSci, an AI-powered provider of predictive solutions for healthcare, has been named a “cool vendor” in a Gartner report (October 2019). Earlier this year, the company was recognized by Microsoft as a finalist of their Health Partner of the Year Award and winner of the HIMSS Innovation Award.
Databricks, a data processing and analytics platform with a strong focus on AI and machine learning, recently raised $400 million in a series F funding round. This puts the company value at $6.2 billion. Databricks plans to use the money to hire more engineers to accelerate R&D.
Microsoft has invested $1 billion in OpenAI, which by the way is no longer “open.” Founded in 2015 by Elon Musk and Sam Altman, OpenAI recently restructured into a for-profit OpenAI LP so that it could commercialize its AI technologies and attract necessary funding. (Musk left the company a year prior.)
CognitiveScale announced an industry-first product ‒ Cortex Certifai ‒ that offers insights into the black box of machine learning and AI and helps organizations to identify, quantify, and mitigate AI-related risks.