‘Listen, that's not what I'm here for, right?' | Image: Apple
Our early testing has already shown that Siri AI knows when to shut up, and that's very much by design. In an interview with Mostly Human, Apple's Craig Federighi said new Siri won't act all sycophantic like chatbots made by OpenAI, Google, and others.
"As you may know, if you use many of the existing chatbots, they're really focused on engagement to a large degree," said Federighi who is responsible for software at Apple. "And sycophancy, right? They kind of want to pull you in. They might encourage you to reveal things about yourself, and then use that as a basis to establish a connection."
Apple purposely took a different approach with …
Read the full story at The Verge.
iPhone owners are getting real, native AI photo editing for the first time.
The most popular camera in the world just got its first set of serious AI photo editing features, and I don't think any of us are ready.
As far as AI photo editing goes, the new features in iOS 27 are pretty tame compared to what you can do on, say, Google's Pixel phones. But for the iPhone, they represent a tipping point in what the native photos app allows you to do to your photos. I mean memories. I mean, I don't know anymore.
These new features are part of the iOS 27 developer beta right now, so bear in mind that Apple may continue making tweaks to them before they're released to the general public. There are three, or maybe two and a …
Read the full story at The Verge.
Concept art from Dear Upstairs Neighbors that used to train custom builds of Google’s Veo and Imagen models. | Image: Google DeepMind
For all the noise that's been made about how generative AI is poised to revolutionize the filmmaking industry, there haven't really been any projects created with the technology that felt like the sort of entertainment people would pay to see. Most AI firms' video models are still only capable of churning out short bursts of visually inconsistent footage. And some of Hollywood's biggest AI partnerships have suddenly evaporated in ways that make it seem like studios might not be able to rely on the new technology coming out of Silicon Valley. For the most part, short-form video slop appears to be the only thing that major production houses ar …
Read the full story at The Verge.
The ruling holds that a company that designs, trains, operates, and manages an AI system must assume legal liability for any damages caused by the responses it generates.
The investigation could lead to increased regulatory scrutiny on AI companies, impacting innovation, transparency, and public trust in AI technologies.
The post OpenAI under investigation by coalition of state attorneys general appeared first on Crypto Briefing.
The investigation into OpenAI could set a precedent for AI accountability, impacting industry regulations and corporate leadership responsibilities.
The post OpenAI subpoenaed for documents on user impact and activities appeared first on Crypto Briefing.
Extremely powerful large language models (LLMs) still operate as though they’re typing on a keyboard, processing workloads in a simple left-to-right fashion. But in locally-run, single-user scenarios, this sequential processing can leave graphics processing units (GPUs) and tensor processing units (TPUs) underutilized.
Google is betting that DiffusionGemma can get around this bottleneck. The new experimental open model generates text “exceptionally fast,” creating entire blocks of text simultaneously through diffusion techniques rather than through token-by-token processing. The company says this technique results in 4x faster inference compared to auto-regressive models that rely on sequential processing.
It can also save users money. Technology analyst Carmi Levy noted that existing pay-per-token monetization models “penalize the use of less than optimally efficient AI solutions.”
But DiffusionGemma “could herald a new generation of task-defined, efficient solutions that can enable e
Extremely powerful large language models (LLMs) still operate as though they’re typing on a keyboard, processing workloads in a simple left-to-right fashion. But in locally-run, single-user scenarios, this sequential processing can leave graphics processing units (GPUs) and tensor processing units (TPUs) underutilized.
Google is betting that DiffusionGemma can get around this bottleneck. The new experimental open model generates text “exceptionally fast,” creating entire blocks of text simultaneously through diffusion techniques rather than through token-by-token processing. The company says this technique results in 4x faster inference compared to auto-regressive models that rely on sequential processing.
It can also save users money. Technology analyst Carmi Levy noted that existing pay-per-token monetization models “penalize the use of less than optimally efficient AI solutions.”
But DiffusionGemma “could herald a new generation of task-defined, efficient solutions that can enable e