Opinion: "Help my daughter write a letter" is not the same as "Help me with boring busywork."

BambooHR’s 2024 Return to Office report details findings on employee and employer sentiment surrounding in-office and remote work.

Amazon released their sustainability report covering the whole of 2023 on July 9th 2024, Google released theirs on July 2nd, and Microsoft…

Maybe the future: Deaddit - a version of Reddit where all the posters are LLMs talking to each other: https://www.deaddit.xyz/ I especially like… | 42 comments on LinkedIn

When you make mean remarks to an LLM, it is not the AI that gets hurt—it's you.

As we wrote last week, there are some major changes coming to the way internet emissions are calculated. With improved data sources and research we now have more accurate data to work with. At Wholegrain we’ve always compared internet emissions to those from other sectors and countries and we have been busy updating them inline […]

Generative AI has a Sustainability problem – across environment, cost and continuing to meet expectations. Many companies are racing to implement GenAI in their projects, lured by its hyped potential to revolutionise industries. However, in applying GenAI to enterprise implementations, I am seeing first-hand the sustainability challenges threatening to implode the first generation of this technology. This blog talks about what I hope will rise from the ashes of such an implosion.

What exists in the space between riffing and ripping

Explore advanced methods for boosting product quality using large language models (LLMs), focusing on Retrieval-Augmented Generation (RAG). Learn how integrating search results can enhance your product's features and user experience.

Every year summers are hotter and heat waves more frequent, with cities suffering most. A network of climate shelters in Barcelona isn’t only making people m...

OpenAI just announced a new search tool. Its demo already got something wrong.

In partnership with Fast Company, explore design principles and prototypes for giving users more transparency when engaging with AI-generated content.

A fresh look at the CSS grid template areas and how to take advantage of its full potential today.

This in-depth guide takes you through the three crucial phases of conversational search, revealing how users express their needs, explore results, and refine their queries. Learn how AI agents can overcome communication barriers, personalize the search experience, and adapt to evolving user intent.

I speak and write about design, front-end code, leadership, and (occasionally) math.

How to use knowledge graphs with retrieval augmented generation (RAG) to organize large content repositories.

The Automation Paradox is that the better our machines get, the more we struggle when they fail. When heading out for a hike in the woods, it's tempting to skip the map and compass and rely on our phones and apps for navigation. Yet when we encounter no signal or lose power, we can find ourselves in a sticky situation. Or perhaps, like me, you've come to rely on popping your destination into the satnav or Google Maps whenever you get in the car and have nearly forgotten the ability to navigate without it. These situations illustrate the paradox of automation, where the more sophisticated and automated our machines and technologies become, the more bewildered we find ourselves when they inevitably fail. Or: the smarter the machines get, the dumber we might get. In his book Messy, Tim Harford suggests three strands to the paradox as our machines get more sophisticated: Automation covers up our mistakes, hiding our incompetence, meaning we may not learn to correct ourselves—consider autocorrect cleaning up our typos as we go. When we rely on automation, we get less practice for our skills, so even highly skilled individuals may find their expertise diminishing—perhaps you've found yourself using your phone calculator for a trivial calculation. When the easy scenarios are taken care of, failures may occur in complex or unpredictable ways that we may find especially difficult to recover from—like a subtle but persistent failure in the steering of a passenger plane, recovering from a skid on an icy road, or when you're deeply lost in the wilderness. More sophisticated technology can even make it useless or more dangerous when it fails. Older cars used to be reparable forever. Now, if your vehicle fails, it's likely to need plugging in at the dealership to figure out what's up. How many electronic devices are thrown away because somewhere inside, some tiny loose connection or component makes the whole thing worthless? Were pilots and flight crews better prepared and able to improvise before the autopilot became ubiquitous? I often wish our devices would fail more like an escalator or an electric toothbrush. If an escalator fails, you can still walk up it. If your electric toothbrush dies, you can still use it to brush your teeth. These could be called Technology-Enhanced Products, perhaps. But when most of our devices die, they're often rendered worthless. Automation and sophisticated machines help me so much. I did use Grammarly to help check this post. I use Google Maps nearly every time I put in my destination to home, and I often use a calculator to check my maths. But I do pay attention to grammar corrections, bring a paper map when I can, and keep trying to do the maths in my head. But as Tim Harford explains it, we still face "the paradox of automation: the better the machines get, the more bewildered we are when the machines fail." Also see: The bus factor Normalisation of deviance Chaos monkey Know your tech Jevon's paradox The law of unintended consequences The Dunning-Kruger effect (send me proof of purchase of Big Ideas Little Pictures, and I'll send the sketch to you) More paradoxes: The coastline paradox The transparency paradox The Abilene paradox The paradox of choice The liar paradox Tolkein-style landscape inspired by the excellent Lord of Maps.

And your free copy of 'A Glossary for the Appreciation of Life: Part One (A-K)'

Google developers for the open source language Go has started using Project Oscar to build AI agents to manage its issue tracking.

AI interview services say they’re eliminating bias — but not everyone agrees.

Episode 132

OpenAI's work seeks to give people a framework to train models to better explain how they arrived at particular answers.

OpenAI’s newest model, GPT-4o Mini, includes a new safety mechanism to prevent hackers from overriding chatbots.

The White House’s voluntary AI commitments have brought better red-teaming practices and watermarks, but no meaningful transparency or accountability.

Explore how technical and social structures co-evolved over five centuries in this large-scale research visualization.

We cannot let this fever run its course

When I first used Dall-E in January 2021, I input some text, I think it was a resin chair inspired by a cactus (I had Gaetano Pesce on my mind). It gave me an output that genuinely rocked me. I was testing this mental model that many people have for image generation that it’s basically just collaging existing images together and I realised fast that this was a very bad mental model. The first output blew my mind because it was so unexpected; It created a lot of detail within the image that I didn’t imagine when I wrote the prompt, which I could never find with a search engine. It had interpreted my prompt in a what I perceived as a

The goal is fungibility—to assert equivalence between activities by people or environments so that emissions created over here can be traded and (theoretically) compensated for by actions removing or reducing carbon over there. The means is, of course, commodification. Offsets privatize planetary metabolism.

New paper counts "excess words" that started appearing more often in the post-LLM era.