Google’s latest and greatest Android version is officially now out in the world and available — but if you’re using any phone other than a Pixel, that doesn’t mean much for you just yet.
The reason why is simple: Despite Google officially launching Android 17 and starting to send it out to Android phone-owners this week, it’s up to each individual device-maker to process the software and deliver it to its customers. And outside of Google itself, unfortunately, most Android device-makers are exasperatingly unreliable about making that happen — some of ’em to almost comically bad extremes (insert exaggerated sigh here).
Hold the phone, though — ’cause there is some good news here: While we can’t force any Android phone-maker to start treating software support as a priority, we can get creative and find ways to bring interesting new Android features to devices running older Android versions. In fact, all four of the Android 17 features I called out earlier this week can be emulated on any
Mercury 2's success signals a potential shift in AI market dynamics, challenging Google's dominance and prompting industry-wide strategic responses.
The post Inception Labs’ Mercury 2 AI outperforms Google’s DiffusionGemma: DecryptMedia appeared first on Crypto Briefing.
Mercury 2's success could reshape AI infrastructure, prioritizing parallel processing and altering hardware value in real-time applications.
The post Inception Labs’ Mercury 2 outperforms Google’s DiffusionGemma in the race to replace autoregressive AI appeared first on Crypto Briefing.
The billionaire founder and CEO of the New York-based hedge fund Third Point LLC is deploying tens of millions of dollars into two hyperscaler names. The latest 13F filing from the U.S. Securities and Exchange Commission (SEC) shows that Dan Loeb opened a new stake in Meta (META) in Q1 of this year, accumulating 90,000 […]
The post Hedge Fund Billionaire Pours $190,674,000 Into Google, Facebook and Three Stocks That Have Each Exploded Over 2x Year-to-Date appeared first on The Daily Hodl.
Atlantic reporter Alex Reisner recently uncovered four datasets of music being used to train AI models and made them fully searchable for the public. Two of the sets are absolutely enormous at 12 million and 9 million tracks. The other two are much smaller, but still represent a significant amount of training data at over 100,000 songs each.
According to Reisner, the sets have been downloaded thousands of times and, while it's impossible to know exactly who has used them, Google and Stability have both confirmed they have in research papers. Some of the sources, like the Free Music Archive dataset, are free to stream for personal use but re …
Read the full story at The Verge.
A new Android banking trojan is targeting 217 banking and cryptocurrency apps while giving attackers broad control over infected devices. The malware is called Rokarolla and is distributed through malicious websites that disguise it as popular applications such as TikTok and Google Chrome, reports the mobile cybersecurity firm Zimperium. Zimperium says Rokarolla is designed to […]
The post Hackers Targeting 217 Android Finance Apps, Draining PINs, Patterns and Passwords: Zimperium appeared first on The Daily Hodl.
The ARD standard could redefine enterprise AI integration, potentially marginalizing non-compliant tools and boosting major backers' market dominance.
The post Google, Microsoft, and Salesforce back new AI software standard to counter OpenAI and Anthropic appeared first on Crypto Briefing.
Enterprises implementing agentic AI face a challenge: Which tools should they allow their agents to use, where can they be found, and how can they be used safely? A new protocol, Agentic Resource Discovery, or ARD, aims to let agents answer those questions for themselves. Behind it are Google, Microsoft, Cisco, Nvidia, Salesforce and others.
ARD aims to standardize the way that tools and services are shared across systems within a corporate domain. For example, when investigating a production problem, an agent may want to query engineering documentation and open support tickets, deployment history and observability systems, all of which could be managed by different registries and across different silos. There is no common layer that pulls them together. ARD has been designed to be that layer.
It operates across two levels. Catalogs and Registries. In the first, an organization publishes a catalog setting out its available capabilities. The Registries layer act as a form of search engi