Oracle Forms New Cloud and AI Organization

Oracle has formed a new organization, focused on the cloud and AI. Oracle has been making significant headway in the cloud market, although it still lags behind market leaders AWS, Microsoft Azure and Google Cloud. Nonetheless, the company is doubling down on its cloud and AI business, and has scored some big wins against its bigger rivals. Link

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Hello Mainframe, Our Old Friend

WSJ: “The mainframe is hardly a relic of a bygone area. In many industries, it remains critical for storing and processing a company’s most sensitive data and serves as a strategic component of hybrid cloud models, according to a recent survey.” Link

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DecisionCAMP Monthly Session on Jan 19

Join DecisionCAMP Monthly Zoom Session on Jan 19 at 12:00 PM EST.  “Kogito: Cloud-native Business Automation” presented by Mario Fusco and Matteo Mortari, Red Hat. A Zoom invite is available from our Slack channel 

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Jan 14 – World Logic Day

On 14 January 2021, we celebrate World Logic DayUNESCO proclaimed World Logic Day in 2019, in association with the International Council for Philosophy and Human Sciences (CIPSH), to enhance public understanding of logic and its implications for science, technology and innovation. There is a virtual celebration in Vienna, the city of Kurt Gödel and Ludwig Wittgenstein – Link

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AI is not equal to ML

Alain Chabrier from IBM Decision Optimization team in his Medium.com article argues that not only “AI != ML” pointing to the difference between Data-driven and Knowledge-driven decision models. He even claims that “Decision Optimization has more impact on the real world than ML“.  “Let’s be careful when writing or reading about AI Ethics, AI Fairness, AI Robustness, AI Explanability, etc.. Check whether this is about AI in general or only about ML. The well known concerns about ML fairness and explanability do not apply to Decision Optimization. Let’s not, at the end, conclude that AI does not work as it promised, if, in fact, only one particular technique or technology is not working as it promised.Link

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Insights for AI from the Human Mind

Artificial intelligence has recently beaten world champions in Go and poker and made extraordinary progress in domains such as machine translation, object classification, and speech recognition. However, most AI systems are extremely narrowly focused. AlphaGo, the champion Go player, does not know that the game is played by putting stones onto a board; it has no idea what a “stone” or a “board” is, and would need to be retrained from scratch if you presented it with a rectangular board rather than a square grid.” To build AIs able to comprehend open text or power general-purpose domestic robots, we need to go further. A good place to start is by looking at the human mind, which still far outstrips machines in comprehension and flexible thinking. This CACM article offers 11 clues drawn from the cognitive sciences—psychology, linguistics, and philosophy. Link

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Controversial rating of programming languages

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Ilya Sutskever: Fusion of Language and Vision in 2021

Ilya Sutskever, the Chief scientist of OpenAI: “In 2021, language models will start to become aware of the visual world… This ability to process text and images together should make models smarter. Humans are exposed to not only what they read but also what they see and hear. If you can expose models to data similar to those absorbed by humans, they should learn concepts in a way that’s more similar to humans. This is an aspiration — it has yet to be proven — but I’m hopeful that we’ll see something like it in 2021.Link

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Oracle Prediction: 80% of Enterprise IT Will Move To The Cloud By 2025

This one of Oracle recently made 10 cloud predictions about the nearest future. The reason is that second-generation, enterprise-grade cloud architectures, plus the extreme automation of platform, will multiply the cost savings of the cloud, while letting enterprise IT organizations meet their commitments for effectiveness, efficiency, and business continuity. Link

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Recent Advances in Google Translate

Google Translate was introduced in 2016 and it enabled great improvements to the quality of translation for over 100 languages since then. In this post Google Research describes how recent advances in machine learning drive improvements to automated translation. Link

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