OLDaily

US government to make all research it funds open access on publication
John Timmer, Ars Technica, 2022/09/02

As announced by the White House Office of Science and Technology Policy (OSTP), "Starting in 2026 any scientific publication that receives federal funding will need to be openly accessible on the day it's published." That's four years away and as we know a lot can happen in that time. But it's still good news and something I think will influence Canadian policy as well. "When research is widely available to other researchers and the public, it can save lives, provide policymakers with the tools to make critical decisions, and drive more equitable outcomes across every sector of society."

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About CRDTs
crdt.tech, 2022/09/02

Boris Mann referenced Conflict-free Replicated Data Type (CRDT) in a post yesterday and while the specific presentation isn't available, it's worth mentioning this concept as part of the broader distributed network technology architecture. "CRDTs ensure that, no matter what data modifications are made on different replicas, the data can always be merged into a consistent state." See also Wikipedia and this Medium post by Nezih Yigitbasi in 2015.

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Storage Layer Maximalism
Jonathan Victor, NFT.Storage, 2022/09/02

An non-fungible token (NFT) is essentially a blockchain record that points to a digital resource. The point being made in this fairly technical post is that "your NFT should point at a thing, not point at a location." What that means, in practice, is that the record shouldn't point to a URL or an internet address, because these can (and often do) change. Instead, it should reference the digital hash of the resource, a content-based address produced using a cryptographic algorithm. Such resources can be uploaded and stored using a distributed network such as the interplanetary file system (IPFS). Via Boris Mann.

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The AI Researcher Giving Her Field Its Bitter Medicine
Max G. Levy, Anima Anandkumar, Quanta Magazine, 2022/09/02

If you look into the mathematics of deep learning AI algorithms, you find that a lot of it is based on calculations using matrices (two dimensional grids of values). That's where the Stanford AI course began, for example. But this limits the complexity AI can comprehend, as Anima Anandkumar explains. "In practice, matrix methods in machine learning can't effectively capture higher-order relationships." Instead, "with their multiple dimensions and flexibility, tensors seem like a natural fit for higher-order problems in AI." But as capacity increases, the questions become more urgent. "It's always important to question how our work is going to impact the world... so much of the way we teach in universities is derived from military school. Engineering came from that background, and some of it lingers. Like thinking that scientists and engineers should focus on the technical stuff and let others take care of the rest. It's wrong. We all need humane thinking." See also: Building Neural Networks with Tensorflow.

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I Wrote a Book with GPT-3 AI in 24 Hours — And Got It Published
2022/09/02

This post about Jukka Aalho's publication may say more about the publisher's review process than it does about AI, but nonetheless the trend is clear: we may soon be able to compose large complex works more easily with AI than we can manually. I can imagine, for example, that I could just take my full set of clips from my bikepacking trip and have the AI professionally produce a nice set of videos (to be clear: that's not what I did). And the same with writing - I can imagine a time where I feed my 36,000 OLDaily posts into an AI and have it auto-generate some treatises representing my thoughts about knowledge, ethics and the future of technology (and with the right clips library and lots of voice samples, it could convert those into a series of accessible videos). If you aren't thinking along these lines, in my view, you aren't grasping the real potential of the technology ahead of us.

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Controversial AI-generated artwork takes home first place at Colorado State Fair
Noel Brennan, 9News, 2022/09/02

Remember when people were saying that AI would never replace people employed in the creative industries? It feels like yesterday. Well, now people are saying "We're watching the death of artistry unfold right before our eyes — if creative jobs aren't safe from machines, then even high-skilled jobs are in danger of becoming obsolete." This may be true, though it's something that will take decades to fully resolve. Meanwhile, we as educators have to think are about how we want people to prepare for a future where traditional employment becomes a thing of the past. Meanwhile, some of the reactions will be pretty, um, colourful. See also: Vice.

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