You might be keenly interested to know that this eagerness to produce responses is something tuned into AI. The AI maker has made various computational adjustments to get the AI to press itself to respond. Why so? Because people want answers. If they aren’t getting answers from the AI, they will go someplace else. That’s not good for the AI maker since they are courting views.
There is a ton of research taking place about AI hallucinations. It is one of the most pressing AI issues of our time.
AI hallucinations are considered a scourge on the future of generative AI and LLMs. Sadly, the state-of-the-art AI still has them, for example, see my analysis of OpenAI’s most advanced ChatGPT or new model o1 that still indeed emits AI hallucinations at the link here. They are like the energy bunny and seem to just keep running.
A recent study by the Baycrest Centre for Geriatric Care reveals that an area of the brain distinct from the stroke lesion may play a significant role in causing the life-altering symptoms with which survivors are often left, which can include severe challenges with speech, mobility and cognition. These results provide hope that innovative, non-invasive treatments could help improve or even fully reverse post-stroke symptoms.
Strokes (which more than 100,000 Canadians suffer every year) leave behind an area where brain cells have died, called a lesion. However, this cannot explain the widespread consequences of stroke, limiting scientists’ and clinicians’ ability to treat them.
The study, titled “Secondary thalamic dysfunction underlies abnormal large-scale neural dynamics in chronic stroke,” published in the journal Proceedings of the National Academy of Sciences, reveals that degeneration of the thalamus—an area of the brain distinct from the stroke lesion—is a significant contributor to post-stroke symptoms.
An international research team has for the first time designed realistic photonic time crystals–exotic materials that exponentially amplify light. The breakthrough opens up exciting possibilities across fields such as communication, imaging and sensing by laying the foundations for faster and more compact lasers, sensors and other optical devices.
“This work could lead to the first experimental realization of photonic time crystals, propelling them into practical applications and potentially transforming industries. From high-efficiency light amplifiers and advanced sensors to innovative laser technologies, this research challenges the boundaries of how we can control the light-matter interaction,” says Assistant Professor Viktar Asadchy from Aalto University, Finland.
The study is published in the journal Nature Photonics.
Massgrave, a piracy group developing activation scripts for Microsoft products, claims to have discovered a new method to permanently activate “almost any version of Windows and Office.”
This group is behind the MAS (Microsoft Activation Scripts) project, which develops piracy tools to activate various versions of Microsoft Windows operating systems and Office products. Unauthorized software license manipulation is illegal in most jurisdictions.
“Our team has successfully cracked almost the entire Windows/Office software licensing protection,” the group announced on social media.
The AI race is heating up! In this video, we delve into the competition between Nvidia’s Llama-3.1 and OpenAI’s GPT-4. Discover how these two AI giants are revolutionizing the field of large language models (LLMs) and reshaping AI performance benchmarks. From Nvidia’s groundbreaking Llama-3.1 Nemotron to GPT-4’s advanced video generation capabilities, we analyze their strengths, use cases, and potential to lead the AI revolution.
Topics covered:
Nvidia Llama-3.1 vs. OpenAI GPT-4: Performance benchmarks. How to use Nvidia Llama-3.1 Nemotron-70B AI in video generation: OpenAI’s GPT-4 and Nvidia AI animation. Nvidia AI benchmarks, GPUs, and requirements. OpenAI vs. Nvidia: Who’s winning the AI race? Llama GPU requirements and running Llama without a GPU Stay tuned to learn which of these tech titans might dominate the future of AI innovation!
Queries: the AI race. the race AI cover. the first AI race. to dominate the AI race. who is winning the AI race. who will win the AI race. off to the races AI cover. nvidia llama 3.1 nvidia llama 3.1 nemotron. nvidia llama 3.1 nemotron 70 how to use nvidia llama 3.1 openai’s gpt-4 nvidia AI nemo. nvidia AI animation. nvidia AI benchmarks. gpt4all vs llama. openai gpt 4 gpt-4 video generation. openai h100 openai nvidia. openai’s gpt-3.5 gpt 4 vs llama. openai 4 openai gpu. gpt 3 or 4 4 gpt ai. openai nvidia gpu. nvidia AI performance. nvidia llm. llm nvidia. how to use nvidia. llama-3.1-nemotron-70b-instruct. nvidia llama. llama gpu. nvidia llama 3.1 api. nvidia AI llama 3.1 llama nvidia. llama without gpu. llama requirements gpu. openai nvidia. nvidia gpt. openai nvidia gpu. openai’s gpt-4 openai’s gpt-4 gpt4 vs llama. gpt-4 vs llama. 4 gpt ai. Nvidia AI Nemotron. OpenAI GPT-4 applications. GPT-4 vs Llama-3.1 detailed review. Nvidia AI advancements 2024 OpenAI’s GPT-3.5 vs GPT-4 comparison. Future of LLMs: Nvidia vs OpenAI AI tools for video generation. Nvidia AI GPUs and requirements. Who will win the AI race? Nvidia vs OpenAI Nvidia Llama-3.1 vs GPT-4 comparison. OpenAI GPT-4 vs Nvidia Llama performance. Nvidia Llama-3.1 Nemotron-70B explained. How to use Nvidia Llama-3.1 AI model. AI race 2024: Nvidia vs OpenAI showdown. GPT-4 video generation vs Nvidia AI animation. Nvidia AI benchmarks and performance in 2024 Llama GPU requirements: Can you run it without a GPU? What is Nvidia Llama-3.1 Nemotron? Nvidia Llama-3.1 Nemotron-70B vs GPT-4: Which is better? AI race: Who will dominate, Nvidia or OpenAI? How to use Nvidia Llama-3.1 API for AI projects. GPT-4 video generation: Is OpenAI leading the AI race? Nvidia AI vs OpenAI: Benchmarks and features compared. Llama-3.1 vs GPT-4: Pros, cons, and use cases. Nvidia AI animation and OpenAI video generation tools. Best GPU for running Nvidia Llama models. OpenAI H100 and Nvidia Llama: A performance comparison. Nvidia AI performance benchmarks: 2024 updates.
An optical lattice clock is a type of atomic clock that can be 100 times more accurate than cesium atomic clocks, the current standard for defining “seconds.” Its precision is equivalent to an error of approximately one second over 10 billion years. Owing to this exceptional accuracy, the optical lattice clock is considered a leading candidate for the next-generation “definition of the second.”
Professor Hidetoshi Katori from the Graduate School of Engineering at The University of Tokyo has achieved a milestone by developing the world’s first compact, robust, ultrahigh-precision optical lattice clock with a device capacity of 250L.
As part of this development, the physics package for spectroscopic measurement of atomic clock transitions, along with the laser and control system used for trapping and spectroscopy of atoms, was miniaturized. This innovation reduced the device volume from the traditional 920 to 250 L, approximately one-quarter of the previous size.
Discover how Artificial Intelligence is revolutionizing the field of cardiology, offering new perspectives and solutions that were once considered impossible.
The ICI Meeting 2024 is an acclaimed forum which aims to explore fuel, spark and be involved in the innovations that will shape the future of our cardiovascular systems.
