HP Z6 G5 A Makes For An Incredibly Powerful AMD Workstation For Creators & Developers

Since the release of the Threadripper 7000 series on 20 November I’ve carried out and published many benchmarks of these new HEDT/PRO CPUs including the flagship AMD Ryzen Threadripper PRO 7995WX featuring 96-cores / 192-threads. All of my Threadripper PRO 7995WX benchmarks have been carried out using an HP Z6 G5 A workstation and it’s proven to be an outright beast for creators, software developers, and others needing immense multi-threaded capabilities at your finger tips. Here’s more about my experience with this new high-end HP workstation.

Source: Phoronix – HP Z6 G5 A Makes For An Incredibly Powerful AMD Workstation For Creators & Developers

How to Install Netdata Monitoring Software on AlmaLinux 9

Netdata is an open-source, extensible, and real-time monitoring system for servers, containers, and applications. Follow our guide to install Netdata with Nginx as a reverse proxy on the AlmaLinux 9 server.

The post How to Install Netdata Monitoring Software on AlmaLinux 9 appeared first on Linux Today.



Source: Linux Today – How to Install Netdata Monitoring Software on AlmaLinux 9

[$] Project Bluefin: A customized Fedora Silverblue desktop image

So-called “immutable” Linux distributions have been in development for
some time, but (unless you count Chrome OS) haven’t gained much traction. Project Bluefin, is a heavily
customized set of Fedora
Silverblue
images coming from the Universal Blue community; they are
designed to deliver a reliable Linux desktop that’s as easy to use as a
Chromebook but more customizable. Bluefin’s mission is to change up
the desktop experience and attract a new generation of open-source
contributors with a “cloud-native”
take
on developing and delivering the operating system.

Source: LWN.net – [$] Project Bluefin: A customized Fedora Silverblue desktop image

Red Hat Looks For Feedback On Its New Initoverlayfs File-System Proposal

Red Hat engineers have been developing Initoverlayfs as a scalable initial file-system. The code is currently in early form and the developers are still looking for feedback from the community as well as figuring out whether it properly belongs in kernel or user-space…

Source: Phoronix – Red Hat Looks For Feedback On Its New Initoverlayfs File-System Proposal

Linux 6.8 Will Make It More Clear When x86 32-bit Support Is Disabled

With Linux 6.7 there’s now support for enabling/disabling 32-bit program support at boot-time. The “ia32_emulation=” argument can be used for enabling/disabling 32-bit user-space program support and the ability to support 32-bit system calls. Right now when forcing off the x86 32-bit support it can be confusing if the user is unaware as no warning is currently provided, but that is about to change…

Source: Phoronix – Linux 6.8 Will Make It More Clear When x86 32-bit Support Is Disabled

FFmpeg Lands CLI Multi-Threading As Its "Most Complex Refactoring" In Decades

The long-in-development work for a fully-functional multi-threaded FFmpeg command line has been merged! The FFmpeg CLI with multi-threaded transcoding pipelines is now merged to FFmpeg Git ahead of FFmpeg 7.0 releasing early next year. FFmpeg is widely-used throughout many industries for video transcoding and in today’s many-core world this is a terrific improvement for this key open-source project…

Source: Phoronix – FFmpeg Lands CLI Multi-Threading As Its “Most Complex Refactoring” In Decades

Intel Visual Sensing Controller Enablement Work Continues For Linux 6.8

Linux 6.6 brought an initial Intel Visual Sensing Controller “IVSC” driver. The Intel IVSC drivers have long been out-of-tree for use with Alder Lake laptops and newer. Linux 6.7 brought the La Jolla Cove Adadpter driver code as part of the IVSC controller. With Linux 6.8 there’s yet more work landing on the IVSC front…

Source: Phoronix – Intel Visual Sensing Controller Enablement Work Continues For Linux 6.8

Cling 1.0 Released For Interactive C++ Interpreter

Cling 1.0 was released this week for this open-source interactive C++ interpreter that builds atop LLVM/Clang. Cling is implemented as an extension to LLVM/Clang to serve as an interpeter leveraging the read-eval-print loop (REPL) concept and relies on just-in-time (JIT) compilation…

Source: Phoronix – Cling 1.0 Released For Interactive C++ Interpreter

AI isn’t just robots: How to talk to young children about AI

Young children have a unique perspective on the world they live in. They often seem oblivious to what’s going on around them, but then they will ask a question that makes you realise they did get some insight from a news story or a conversation they overheard. This happened to me with a class of ten-year-olds when one boy asked, with complete sincerity and curiosity, “And is that when the zombie apocalypse happened?” He had unknowingly conflated the Great Plague with television depictions of zombies taking over the world.

Child with tablet.
Photo by Patricia Prudente.

How to talk to young people about AI

Absorbing media and assimilating it into your existing knowledge is a challenge, and this is a concern when the media is full of big, scary headlines about artificial intelligence (AI) taking over the world, stealing jobs, and being sentient. As teachers and parents, you don’t need to know all the details about AI to answer young people’s questions, but you can avoid accidentally introducing alternate conceptions. This article offers some top tips to help you point those inquisitive minds in the right direction.

Child with tablet.
Photo by Kelly Sikkema.

AI is not a person

Technology companies like to anthropomorphise their products and give them friendly names. Why? Because it makes their products seem more endearing and less scary, and makes you more likely to include them in your lives. However, when you think of AI as a human with a name who needs you to say ‘please’ or is ‘there to help you’, you start to make presumptions about how it works, what it ‘knows’, and its morality. This changes what we ask, how much we trust an AI device’s responses, and how we behave when using the device. The device, though, does not ‘see’ or ‘know’ anything; instead, it uses lots of data to make predictions. Think of word association: if I say “bread”, I predict that a lot of people in the UK will think “butter”. Here, I’ve used the data I’ve collected from years of living in this country to predict a reasonable answer. This is all AI devices are doing. 

Child with phone.
Photo by bruce mars.

[AI] does not ‘see’ or ‘know’ anything; instead, it uses lots of data to make predictions.

When talking to young children about AI, try to avoid using pronouns such as ‘she’ or ‘he’. Where possible, avoid giving devices human names, and instead call them “computer”, to reinforce the idea that humans and computers are very different. Let’s imagine that a child in your class says, “Alexa told me a joke at the weekend — she’s funny!” You could respond, “I love using computers to find new jokes! What was it?” This is just a micro-conversation, but with it, you are helping to surreptitiously challenge the child’s perception of Alexa and the role of AI in it.

Where possible, avoid giving devices human names, and instead call them ‘computer’, to reinforce the idea that humans and computers are very different.

Another good approach is to remember to keep your emotions separate from computers, so as not to give them human-like characteristics: don’t say that the computer ‘hates’ you, or is ‘deliberately ignoring’ you, and remember that it’s only ‘helpful’ because it was told to be. Language is important, and we need to continually practise avoiding anthropomorphism.

AI isn’t just robots (actually, it rarely is)

The media plays a huge role in what we imagine when we talk about AI. For the media, the challenge is how to make lines of code and data inside a computer look exciting and recognisable to their audiences. The answer? Robots! When learners hear about AI taking over the world, it’s easy for them to imagine robots like those you’d find in a Marvel movie. Yet the majority of AI exists within systems they’re already aware of and are using — you might just need to help draw their attention to it.

Even better than just calling out uses of AI: try to have conversations about when things go wrong and AI systems suggest silly options.

For example, when using a word processor, you can highlight to learners that the software sometimes predicts what word you want to type next, and that this is an example of the computer using AI. When learners are using streaming services for music or TV and the service predicts something that they might want to watch or listen to next, point out that this is using AI technology. When they see their parents planning a route using a satnav, explain that the satnav system uses data and AI to plan the best route.

Even better than just calling out uses of AI: try to have conversations about when things go wrong and AI systems suggest silly options. This is a great way to build young people’s critical thinking around the use of computers. AI systems don’t always know best, because they’re just making predictions, and predictions can always be wrong.

AI complements humans

There’s a delicate balance between acknowledging the limitations of AI and portraying it as a problematic tool that we shouldn’t use. AI offers us great opportunities to improve the way we work, to get us started on a creative project, or to complete mundane tasks. However, it is just a tool, and tools complement the range of skills that humans already have. For example, if you gave an AI chatbot app the prompt, ‘Write a setting description using these four phrases: dark, scary, forest, fairy tale’, the first output from the app probably wouldn’t make much sense. As a human, though, you’d probably have to do far less work to edit the output than if you had had to write the setting description from scratch. Now, say you had the perfect example of a setting description, but you wanted 29 more examples, a different version for each learner in your class. This is where AI can help: completing a repetitive task and saving time for humans. 

Child with phone.
Photo by zhenzhong liu.

To help children understand how AI and humans complement each other, ask them the question, ‘What can’t a computer do?’ Answers that I have received before include, ‘Give me a hug’, ‘Make me laugh’, and ‘Paint a picture’, and these are all true. Can Alexa tell you a joke that makes you laugh? Yes — but a human created that joke. The computer is just the way in which it is being shared. Even with AI ‘creating’ new artwork, it is really only using data from something that someone else created. Humans are required. 

Overall, we must remember that young children are part of a world that uses AI, and that it is likely to be ever more present in the future. We need to ensure that they know how to use AI responsibly, by minimising their alternate conceptions. With our youngest learners, this means taking care with the language you choose and the examples you use, and explaining AI’s role as a tool.

To help children understand how AI and humans complement each other, ask them the question, ‘What can’t a computer do?’

These simple approaches are the first steps to empowering children to go on to harness this technology. They also pave the way for you to simply introduce the core concepts of AI in later computing lessons without first having to untangle a web of alternate conceptions.


This article also appears in issue 22 of Hello World, which is all about teaching and AI. Download your free PDF copy now.

If you’re an educator, you can use our free Experience AI Lessons to teach your learners the basics of how AI works, whatever your subject area.

The post AI isn’t just robots: How to talk to young children about AI appeared first on Raspberry Pi Foundation.



Source: Raspberry Pi – AI isn’t just robots: How to talk to young children about AI