-
Recently Browsing 0 members
- No registered users viewing this page.
-
Similar Content
-
New study “proves” you can get adequate exercise from your man cave with VR
By zikalify,
- meta
- meta quest
- (and 6 more)
- 3 replies
- 3 views
-
Meta scores major victory as FTC drops case against Within acquisition
By Usama Jawad96,
- 3 replies
- 4 views
-
- 5 replies
- 3 views
-
- 5 replies
- 20 views
-
Microsoft reveals an interesting deal for 'The Walking Dead' fans in the Windows Store
By Usama Jawad96,
- microsoft
- the walking dead
- (and 10 more)
- 10 replies
- 390 views
-
-
Posts
-
By Lamp0 · Posted
Its in 3D now! -
By +Edouard · Posted
The laptop in the bedroom is an Acer with i7-10510U CPU. Acer's website states they will not be upgrading it so I had little choice other than disable secure boot. I know next to nothing on these matters so hopefully it will be fine. -
By Karthik Mudaliar · Posted
GitHub removes manual model selection from Copilot free and student plans by Karthik Mudaliar GitHub is removing the ability to manually select an AI model from its Copilot Free and Student plans, making its automatic routing system the default and only way to choose a model. This means users on these tiers will no longer be able to deliberately select a particular OpenAI, Anthropic, Google, or Microsoft model for a task. In its announcement, GitHub said Copilot Auto will dynamically choose what it considers the best model for each request. Free and Student accounts will retain access to models from multiple families, although the available selection will continue to depend on the restrictions attached to each plan. GitHub did not identify a fixed pool of models that Auto will always use, and its documentation warns that model availability can change over time. GitHub describes Auto as more than a random fallback system. On supported surfaces, its task-optimization technology evaluates the complexity of a request alongside real-time information about model health and availability. Straightforward prompts can be routed to faster and less expensive models, while more demanding coding tasks may be sent to higher-cost reasoning models. The company says this approach should reduce rate limiting, latency, and failed requests. Auto generally selects one model along natural prompt-caching boundaries rather than repeatedly switching models during a session, as GitHub found that mid-session changes increased costs without producing sufficient improvements in output quality. Users can still check which model generated a response. In Copilot Chat, the information appears when hovering over an answer, while Copilot CLI and the Copilot cloud agent display the selected model alongside their output. Auto is available in Copilot Chat, Copilot CLI, and the cloud agent, with the exact implementation and release status varying between supported development environments. The latest restriction follows several months of adjustments to Copilot’s individual plans. GitHub temporarily halted new Pro, Pro+, and Student subscriptions in April as it sought to manage demand and service reliability. It later introduced token-based billing and began gradually reopening individual-plan registrations on June 17. Alongside the picker change, GitHub is retiring the “Preview” label from Microsoft-developed models. It argues that the label is no longer necessary because Auto handles model routing and models are continuously updated behind the scenes. -
By thartist · Posted
Look up 'inflation' kid. Ask an AI for the numbers between both games. -
By Karthik Mudaliar · Posted
Google reportedly set to lose two key Gemini and DeepMind researchers to Anthropic by Karthik Mudaliar Google is reportedly preparing to lose two more prominent artificial intelligence researchers, with Gemini contributors Jonas Adler and Alexander Pritzel planning to join rival AI developer Anthropic. According to a report from Bloomberg, both researchers are viewed internally as important contributors to Google’s flagship Gemini model family. Adler worked on Google’s AI coding efforts, while Pritzel was involved in the process used to train AI systems. Neither company has publicly confirmed the moves. The report also does not say when the researchers will formally leave Google or what positions they will hold at Anthropic. Training a large AI model requires decisions covering its architecture, data preparation, distributed computing infrastructure, and post-training methods that shape how the finished system behaves. Researchers with experience operating at the scale of Gemini are consequently difficult to replace quickly. Both Adler and Pritzel have previously contributed to Google DeepMind’s scientific research as well. They are listed among the authors of the company’s work on expanding AlphaFold protein-structure predictions across entire proteomes, alongside AlphaFold researchers including John Jumper. The reported departures arrive shortly after another important change within Google’s Gemini organization. Gemini co-lead Noam Shazeer is leaving Google for OpenAI, after returning to the search company in 2024 through its deal with Character.AI. Shazeer is particularly well known as one of the authors of the Transformer paper, whose architecture became the foundation for most modern large language models. Anthropic, meanwhile, has been recruiting recognizable figures from other leading laboratories. OpenAI co-founder and former Tesla AI director Andrej Karpathy joined Anthropic’s pre-training team in May. His move, followed by the reported recruitment of several Google researchers, suggests Anthropic is strengthening the research teams responsible for the core capabilities of future Claude models rather than concentrating solely on product and enterprise sales. The competition is complicated by the companies’ extensive commercial relationships. Anthropic competes directly with Google’s Gemini models, but it also relies on Google as an infrastructure partner. In April, Anthropic announced an expanded agreement with Google and Broadcom covering multiple gigawatts of next-generation Tensor Processing Unit capacity. TPUs are Google-designed accelerators used to train and run large AI models. via Bloomberg
-
-
Recent Achievements
-
Scoobystu earned a badge
Dedicated
-
Tom Schmidt earned a badge
First Post
-
D0nn13 earned a badge
One Month Later
-
+ChiefOfNeo went up a rank
Rookie
-
Tom Schmidt earned a badge
One Year In
-
-
Popular Contributors
-
Tell a friend
.thumb.png.b7089ebbdf00d96b3b92dddbd04bac02.png)
Recommended Posts