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- 🤖 Google Unveils Cloud TPU v5p
🤖 Google Unveils Cloud TPU v5p
PLUS:Meta Unveils Independent AI-Powered Image Generation Tool
Hyrise AI
December 07, 2023
Welcome, AI Enthusiasts.
Google has unveiled the Gemini large language model alongside its latest Cloud TPU v5p, a successor to the v5e, boasting 8,960 chips and faster interconnectivity at 4,800 Gpbs per chip.
Meta has introduced Imagine with Meta, a standalone generative AI tool allowing image creation from text descriptions.
In today’s issue:
🤖 Google Unveils Cloud TPU v5p: The Pinnacle of AI Accelerators
🦾 Meta Unveils Independent AI-Powered Image Generation Tool
🛠️ 3 New AI tools
💻 Custom prompts ChatGPT and DALL-E 3
🤖 3 Quick AI updates
Read time: 4 minutes.
LATEST HIGHLIGHTS
Image source: Unsplash
To recap: Google has unveiled the Gemini large language model alongside its latest Cloud TPU v5p, a successor to the v5e, boasting 8,960 chips and faster interconnectivity at 4,800 Gpbs per chip. This new TPU offers a 2x improvement in FLOPS and 3x in high-bandwidth memory, significantly outpacing its predecessors. It's projected to train large language models like GPT3-175B 2.8 times faster than the previous v4, promising cost-effectiveness despite its superior performance. However, it's not yet generally available, requiring developers to contact their Google account managers to access it.
The details:
Cloud TPU v5p Specifications: The TPU v5p includes 8,960 chips with enhanced interconnectivity, providing up to 4,800 Gpbs per chip, marking a notable improvement over its predecessors.
Performance Advancements: Compared to the TPU v4, the v5p boasts a 2x improvement in FLOPS and a 3x boost in high-bandwidth memory, enabling it to train large language models like GPT3-175B significantly faster.
Availability: Although the TPU v5p has been announced, it's not yet generally available, and developers interested in utilizing it will need to engage with their Google account manager to access this cutting-edge hardware.
Here is the key takeaway: Google's Cloud TPU v5p marks a significant leap in performance over its predecessors, promising 2x faster training for large language models like GPT3-175B and offering substantial improvements in FLOPS and high-bandwidth memory. However, despite its announcement, the hardware is not yet generally available, requiring developers to engage with their Google account manager for access.
Image source: Unsplash
In Summary: Meta has introduced Imagine with Meta, a standalone generative AI tool allowing image creation from text descriptions. Comparable to DALL-E and powered by Meta’s Emu model, this free-to-use feature generates high-resolution images from prompts, now available beyond messaging platforms. To address concerns about misuse, Meta plans to implement invisible watermarks detectable by specific AI models, aiming to enhance transparency and traceability for AI-generated content. With increasing pressure to differentiate AI-generated works and maintain transparency, regulations and discussions in both China and the US highlight the need for clear markers on content created by generative AI tools.
Key points:
Imagine with Meta Launch: Meta introduces "Imagine with Meta," a standalone generative AI tool enabling image creation through text prompts, similar to DALL-E, powered by Meta's Emu model. It's currently accessible for users in the U.S. and generates four images per prompt.
Watermarking for Transparency: Meta plans to implement invisible watermarks on content generated by Imagine with Meta for increased transparency and traceability. These watermarks, detectable by corresponding AI models, aim to address concerns about content misuse and authenticity.
Pressure for AI Transparency: Recent events, such as concerns about racially biased AI tools and the emergence of Deepfakes, have increased the pressure on tech companies to ensure transparency in AI-generated content. Regulations in China and discussions in the U.S. Senate emphasize the need for clear markers on generative AI content.
Technological Safeguards: Technologies like invisible watermarking, adopted by startups and tech giants, aim to withstand image manipulations, ensuring that markers indicating AI-generated content remain intact despite resizing, cropping, or other modifications. This move reflects efforts to combat the misuse of AI-generated content.
Our thoughts: The introduction of "Imagine with Meta" marks another step in the evolution of generative AI tools, aiming to make image creation more accessible through natural language prompts. While this advancement brings creative potential, it also raises critical concerns about content authenticity and misuse, especially in light of previous controversies around biased AI tools. Implementing invisible watermarks for transparency is a positive move, yet ensuring their resilience against manipulations remains a challenge. The ongoing pressure for transparency in AI content creation underscores the growing need for responsible development and clear identification of AI-generated content to address misuse concerns.
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AI DOJO
ChatGPT
Dreamscape Narration:
Prompt: "Write a descriptive narrative recounting a vivid dream that feels both surreal and thought-provoking, exploring themes of time, identity, and reality."
DALL-E 3
Space Exploration Concept:
Prompt: "Design a series of space exploration vehicles, showcasing innovative designs for spacecraft, rovers, and habitats suitable for diverse extraterrestrial environments."
QUICK BYTES
Vast Data has raised $118 million in a Series E round, valuing the company at $9.1 billion post-money. Specializing in unstructured data storage, the New York-based startup targets AI workloads, offering a unified platform across various clouds and data types. Their positive revenue and growth, with notable clients like Pixar and Zoom, reflect their substantial market presence. The investment aims to fuel expansion, particularly in Asia Pacific, the Middle East, and Europe, positioning Vast Data as a key player in modern data management infrastructure.
Respeecher, a Ukrainian synthetic voice startup, secures $1 million in funding amidst the challenges posed by ongoing conflict. Despite the turmoil in their city, the company's success grows, driven by partnerships like replicating iconic voices for shows and games. The startup's ethical approach involves obtaining consent from rights holders, particularly when recreating voices of deceased actors, engaging families for their valuable insights and approval.
They differentiate by working closely with voice actors, ensuring permission and compensation upfront, even building a library of willing actors for their voice models. While Respeecher missed rapid scaling opportunities in AI, their deliberate pace seems beneficial. Amidst adversity, they've also ventured into assisting individuals who've lost their ability to speak, a less lucrative yet impactful area. This resilience and varied approach have attracted a $1 million pre-Series A investment from notable contributors like Gary Vaynerchuk and several venture funds.
Liquid AI, a new MIT spinoff led by robotics expert Daniela Rus, has secured substantial funding of $37.5 million to pioneer liquid neural networks, an innovative AI model that aims to revolutionize general-purpose AI systems. These networks, conceived by Rus and her team, are smaller, more efficient, and adaptable, providing not only reduced computational needs but also enhanced interpretability and adaptability. The startup envisions applications in various fields, from autonomous driving to weather pattern analysis, aiming to commercialize these cutting-edge AI advancements, competing with models like OpenAI's GPT series. Liquid AI's immediate goals include developing new foundation models beyond GPTs, providing AI infrastructure, and enabling customers to build their own models while emphasizing safety and accountability in large AI systems.
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