Coté

Business spending on AI surged 500% this year to $13.8 billion, says Menlo Ventures - “The report found code generation is the leading use case for generative AI, with more than half of survey responses naming that as a dominant use. Support chatbots came next, at 31%, followed by enterprise search and retrieval, data extraction and transformation, and meeting summarization.” // Once enterprise people are comfortable with using public cloud AI (they are currently not, at scale) things will grow a lot. Then we’ll need a year to see if it’s actually useful (and worth, like, $20 a month per head more in the IT bill). I hope it works! I like the AI stuff.

Gartner forecast dampens cloud repatriation outlook - Pretty thorough round-up of recent analyst stuff, and even the GIECO angle.

What hacks/tips do you use to make AI work better for you? - “Treating [AI chatbots] like a coach - tell it what you’ve done and need to get done, include any feedback you’ve had, and ask it for suggestions. This particularly helps when you’re some kind of neurospicy and ‘regular human’ responses sort of escape you.”

Red Hat to Donate Podman Along With Other Container Tools to CNCF - “Red Hat reports Podman Desktop has been downloaded more than 1.5 million times and like other Red Hat tools is currently optimized to be used in conjunction with Red Hat Enterprise Linux (RHEL). The tools will now be further advanced initially as sandbox-level projects under the auspices of the CNCF."

Alternatives To Typical Technical Illustrations And Data Visualisations - These look cool, but I had to spend a lot of time figuring them out. Bar charts are boring, but they’re efficient. Still, I want to try some of these.

Platform Engineering as a Service - It’s like DevOps, but you centralize and standardize the platform: ‘This is where Platform Engineering comes in. Rather than having each development team own their entire infrastructure stack, platform engineering provides a centralized, productized approach to infrastructure and developer tools. It’s about creating reusable, self-service platforms that development teams can leverage to build, deploy, and scale their applications efficiently. These platforms abstract away the complexities of cloud infrastructure, CI/CD pipelines, and security, enabling developers to focus on writing code rather than managing infrastructure or “glue”.'

Platform Engineering as a Service - It’s like DevOps, but you centralize and standardize the platform: ‘This is where Platform Engineering comes in. Rather than having each development team own their entire infrastructure stack, platform engineering provides a centralized, productized approach to infrastructure and developer tools. It’s about creating reusable, self-service platforms that development teams can leverage to build, deploy, and scale their applications efficiently. These platforms abstract away the complexities of cloud infrastructure, CI/CD pipelines, and security, enabling developers to focus on writing code rather than managing infrastructure or “glue”.'

IMG_0001 - Take a look into random videos from people’s lives from a decade ago: ‘Between 2009 and 2012, iPhones had a built-in “Send to YouTube” button in the Photos app. Many of these uploads kept their default IMG_XXXX filenames, creating a time capsule of raw, unedited moments from random lives.’ // Mesmerizing!

Cloud market share shows vendors eyeing a $1T opportunity - “the revenue shares for our eight cloud companies in the combined IaaS/PaaS cloud market at nearly $300 billion projected for 2024. AWS has 36% of this combined market, Microsoft 23% and Google 7%. Alibaba, Oracle Tencent Huawei and IBM combine for around 14% of the market with “Other” (not shown) at 20%."

- Red Hat acquires tech to lower the cost of machine learning | Computer Weekly - The race to build the private AI stack for enterprises: “All of this translates to lower costs, faster inference and the ability to run AI workloads on a wider range of hardware."

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