The majority of my time as a developer is spent on understanding problems and existing solutions, before deciding on a fitting course of action and implementing it, which is then fun to do.
All the ai code assist hype would be less insufferable if the promotors and managers eager to buy into it showed an inkling of understanding that it takes away little of the hard and tedious work, and mostly replaces the fun work with more hard and tedious work.
For two consecutive quarters, generative #AI dealmaking at the earliest stages has declined, dropping 76% from its peak in Q3 2023 as wary investors sit back and reassess following the initial flurry of capital into the space.
Okay, now this is important. Drop everything you're doing, because Tom7 has released a new video. And oh boy, is it wonderful. 20 minutes won't save your life - and this video demands you sacrifice that time. Now!
»Adobe will Zugriff auf Inhalte von Photoshop-Usern:
Der Konzern hat seine Nutzungsbedingungen aktualisiert. Wer zustimmt, gibt dem Unternehmen das Recht, auf seine Daten zuzugreifen.«
Ich empfehle und nutze schon länger @krita, @GIMP, @inkscape, @Blender und/oder @penpot aber ich bin ja kein Grafikprofi. Abgesehen davon wird selten zugegeben, dass die Fixierung auf einen Hersteller nicht unbedingt professionell ist.
🧵 …und immer noch wird Apple so wie Adobe als professionell und nicht als Spionage oder/und Ausnutzung angesehen. Vom Copyright und Co. sprechen wir hier noch gar nicht, denn dies ist so umgesetzt keine Freiheit.
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»Adobe's new terms of service unacceptably gives them access to all of your projects, for free«
The tricky thing about being a company that I don't trust is that even when you try to clarify something you need to be aware that specificity can sound suss.
"Adobe does not train Firefly Gen AI models on customer content."
The way this is worded does not say your content is not used in training AI models, just that it's - SPECIFICALLY - not used to train "Firefly Gen AI models."
#AI#GenerativeAI#Media#News#Journalism#OpenAI: "Those other deals they did a long time ago? The ones with the likes of Google and Apple and, most particularly, Facebook? They actually have learned lessons from them.
Most crucially: Those deals required publishers to change their business — to create new formats, or make a particular kind of video or story they wouldn't normally make, or to make more of them than they'd normally make. (The one I remember most vividly was Facebook's live video push, which paid publishers like The New York Times to make boring videos.)
But the OpenAI deals, the publishers emphasize, are straightforward licensing deals for stuff they're already making. Nothing bespoke. "It doesn't change the way we operate," one of them tells me.
And that is by far the most common theme you hear when you talk to publishers about these deals. They're something close to free money — for work that was going to get made regardless.
Which means — they say — at the end of these deals, publishers won't have to regret investing in another defunct Big Tech project."
#AI#GenerativeAI#Energy#Automation#WageSlavery#Inequality: "AI is everywhere; AI is here. The story around AI implies that it is here because it’s making things efficient: AI is better at detecting cancerous tumours in some scan images than radiographers, AI is faster at finding legal judgements within case law, AI can make office work more efficient by drafting emails or summarizing information from the web.
However, the story of this efficiency leaves out a discussion of some of the costs of AI. AI is expensive, not cheap. The efficiencies that are promised do not necessarily involve less work and fewer costs – just different work and different costs, some of which will only reveal themselves in time. These costs include:
Increased inequities (including inequitable labour between people ‘in front of’ and ‘behind’ the screen; inequitable opportunities for learning resulting from embedding of AI systems in learning and information infrastructures; environmental and material inequities resulting from the use of scarce natural resources to power ubiquitous technologies)
Shaky institutions that struggle to do things differently
Costly need for highly skilled review of AI outputs
First, we need to understand better what makes AI expensive. Then, we need to consider what factors can actually lead to real efficiency. My research has been examining both the deceptive stories that shape the way AI is described, as well as sociotechnical design considerations that must be taken into account when determining whether the cost of AI is worth it."
Have you ever wished you could understand what your dog is saying? AI could be the answer. The researchers involved in a new study say that AI models like Wav2Vec2 can identify a dog’s “gender, emotion, and breed” based on their bark. To test the accuracy of the models, they used two different sets of data to train the AI models and then compared the results.
One was trained on human speech and then fine-tuned with the barks, while the other was trained only on the barks. The researchers found that the model pre-trained with human speech did better at understanding and identifying the secret language of dogs. BGR has more.