Voyager

#flatpak #wayland #dbus #pidfd #portals

Cisco on Thursday announced an agreement to buy cybersecurity and observability company Splunk for about $28 billion.

The big picture: Legacy tech giants are usually the last to recognize they're being disrupted, but that doesn't seem to be the case with AI.

Expect a lot more of these sorts of mergers, even if the targets aren't AI-native. Details: The $157 per share offer represents over a 31% premium to Wednesday's closing price for Splunk shares.

The last time Splunk traded above $157 per share was in early 2021. It's the networking giant's largest acquisition. Cisco says the merger will add roughly $4 billion in ARR, boosting its subscription and recurring revenue efforts. The purchase price will be financed via a combination of cash and debt, with a final closing by the end of Q3 2024, the company said. What they're saying: "This will help our customers move from threat detection and response to threat prediction and prevention," said Cisco CEO Chuck Robbins during a conference call Thursday morning.

"In terms of observability, our complimentary capabilities will offer observability for the full IT stack, from the application to the network, across hybrid and multi-cloud environments." Editor's note: This story was updated with additional details about the deal.

BadBazaar malware campaigns: ESET researchers have identified two active campaigns targeting Android users with BadBazaar malware, which is attributed to the China-aligned APT group GREF. The campaigns have been active since July 2020 and July 2022, respectively.

Trojanized Signal and Telegram apps: The campaigns distribute BadBazaar malware through malicious apps that mimic Signal and Telegram, called Signal Plus Messenger and FlyGram. The apps are available on Google Play, Samsung Galaxy Store, and dedicated websites. The apps can exfiltrate user data and spy on Signal communications.

Targeting Uyghurs and others: BadBazaar malware has previously been used to target Uyghurs and other Turkic ethnic minorities outside of China. FlyGram malware was also seen shared in a Uyghur Telegram group. ESET telemetry reported detections on Android devices from 16 countries.

cross-posted from: https://psychedelia.ink/post/526424

On Wednesday, OpenAI announced DALL-E 3, the latest version of its AI image synthesis model that features full integration with ChatGPT. DALL-E 3 renders images by closely following complex descriptions and handling in-image text generation (such as labels and signs), which challenged earlier models. Currently in research preview, it will be available to ChatGPT Plus and Enterprise customers in early October.

Like its predecessor, DALLE-3 is a text-to-image generator that creates novel images based on written descriptions called prompts. Although OpenAI released no technical details about DALL-E 3, the AI model at the heart of previous versions of DALL-E was trained on millions of images created by human artists and photographers, some of them licensed from stock websites like Shutterstock. It's likely DALL-E 3 follows this same formula, but with new training techniques and more computational training time.

Judging by the samples provided by OpenAI on its promotional blog, DALL-E 3 appears to be a radically more capable image synthesis model than anything else available in terms of following prompts. While OpenAI's examples have been cherry-picked for their effectiveness, they appear to follow the prompt instructions faithfully and convincingly render objects with minimal deformations. Compared to DALL-E 2, OpenAI says that DALL-E 3 refines small details like hands more effectively, creating engaging images by default with "no hacks or prompt engineering required."

On Wednesday, OpenAI announced DALL-E 3, the latest version of its AI image synthesis model that features full integration with ChatGPT. DALL-E 3 renders images by closely following complex descriptions and handling in-image text generation (such as labels and signs), which challenged earlier models. Currently in research preview, it will be available to ChatGPT Plus and Enterprise customers in early October.

Like its predecessor, DALLE-3 is a text-to-image generator that creates novel images based on written descriptions called prompts. Although OpenAI released no technical details about DALL-E 3, the AI model at the heart of previous versions of DALL-E was trained on millions of images created by human artists and photographers, some of them licensed from stock websites like Shutterstock. It's likely DALL-E 3 follows this same formula, but with new training techniques and more computational training time.

Judging by the samples provided by OpenAI on its promotional blog, DALL-E 3 appears to be a radically more capable image synthesis model than anything else available in terms of following prompts. While OpenAI's examples have been cherry-picked for their effectiveness, they appear to follow the prompt instructions faithfully and convincingly render objects with minimal deformations. Compared to DALL-E 2, OpenAI says that DALL-E 3 refines small details like hands more effectively, creating engaging images by default with "no hacks or prompt engineering required."

Summary: This article provides a brief introduction to commonly used virtual network interface types in Linux, including bridge, bonded interface, team device, VLAN, VXLAN, MACVLAN, IPVLAN, MACVTAP/IPVTAP, MACsec, and more. It explains what these interfaces are, their differences, when to use them, and how to create them. It is a useful resource for anyone with a network background.

Comments: This article is an introduction to Linux interfaces for virtual networking, explaining the fundamentals and providing insights into SR-IOV. It discusses how SR-IOV allows a single hardware device to act as multiple virtual devices, improving performance and reducing overhead. The article also mentions the book 'The Linux Programming Interface' as a resource for learning more about Linux interfaces for virtual networking.

cross-posted from: https://psychedelia.ink/post/526072

My impression of Organic Maps immediately improved when I started driving. It talks! It knows exit numbers! It can tell you which lanes to use! Sure, it isn’t as polished as Google Maps, but all of the functionality is present. The UI is high-contrast and easy to read, although I wish the text showing exit numbers/street names was a little bigger. When you’re simply on the road and following directions, Organic Maps feels every bit as intuitive as Google Maps.

As my fiancee and I prepared to set off into the boonies, I plugged in the address of our hotel. About 45 seconds later, Organic Maps returned the 300-mile route to our destination. It can take a lot longer to calculate longer routes using your phone’s processor instead of a huge cloud server. It didn’t really bother me though; 45 seconds is nothing compared to the 6-hour trip ahead. If that’s the cost of using a maps app that doesn’t spray your personal data all over the internet, I’ll pay it.