Amazon invested another $4B in Anthropic making it a total investment of $8B

Amazon's decision to invest an additional $4 billion in Anthropic, bringing its total investment to $8 billion, reflects its strategic focus on becoming a key player in the generative AI landscape. Although Amazon remains a minority investor, the partnership is significant as Amazon Web Services (AWS) will serve as Anthropic's primary cloud and training partner. Anthropic will now utilize AWS's specialized AI chips, Trainium and Inferentia, to train and deploy its advanced AI models, such as the Claude chatbot.

This investment underscores Amazon's commitment to strengthening its position in the rapidly growing generative AI market, projected to exceed $1 trillion in revenue within a decade. By partnering with Anthropic, Amazon gains access to cutting-edge AI capabilities, such as the recently announced "Computer Use" feature, which allows AI to perform complex tasks on computers, emulating human workflows.

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Application for Mistral AI Startup Program

Are you an AI startup looking to accelerate your growth? Mistral AI’s Mistralship Startup Program is here to help! Join a select 6-month cohort of 10 startups and enjoy:

🌟 30K in credits for Mistral's La Plateforme
🌟 1:1 support from Mistral's expert Solutions & Science team
🌟 Exclusive early access to cutting-edge AI models and products

Eligibility Criteria:
✅ You must apply with a valid business email (e.g., [email protected]).
✅ Your company must have an online presence or website.
✅ Your company must be founded within the last 7 years.
✅ Your company must not have raised a Series B or later funding round (if you have, contact Mistral for alternative options).

Deadline for EMEA Startups: Applications close January 5, 2025. Applications for startups outside EMEA are already open!

Link to application form

OpenAI Shuts Down Sora Access After Artists Released Video-Generation Tool in Protest: ‘We Are Not Your PR Puppets’

OpenAI's early access program for its generative-AI video tool, Sora, has faced backlash from a group of 19 visual artists and filmmakers. They accused OpenAI of exploiting them for free labor, including bug testing and feedback, under the guise of creative partnership. In a public letter, the artists criticized the program as a public relations stunt, claiming the company valued marketing over genuine artist support. The letter also highlighted the imbalance in compensation, as artists contributed to the development of a $150 billion company but received minimal rewards. OpenAI responded by suspending access to Sora, defending the tool's research phase and emphasizing that participation was voluntary. Despite their support for AI as a creative tool, the artists urged OpenAI to be more artist-friendly and transparent. This incident underscores growing concerns over AI's impact on creative industries, particularly as platforms like Sora and Meta's Movie Gen begin to generate realistic videos based on text prompts.

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The State of Generative AI

In 2024, generative AI became a critical focus for enterprises, with spending on AI skyrocketing to $13.8 billion, more than six times the $2.3 billion spent in 2023. This surge signals a shift from experimentation to implementation, as 72% of decision-makers expect broader adoption of generative AI tools. However, despite optimism, over a third of survey respondents still lack a clear plan for AI integration within their organizations, indicating that the transformation is in its early stages.

Key adoption trends highlight several use cases delivering tangible ROI:

• Code copilots lead with 51% adoption, making developers the primary users of AI. GitHub Copilot, for example, is on track for a $300 million revenue run rate.

• Support chatbots follow with 31% adoption, offering 24/7 support for both internal and external customers.

• Enterprise search and retrieval (28% adoption) and data extraction and transformation (27% adoption) reflect a push to unlock knowledge within data silos.

• Meeting summarization tools, like Fireflies.ai and Otter.ai, are used by 24% of enterprises to boost productivity by automating note-taking
  
  Link to full report

China Alibaba Qwen team release model similar to OpenAI o1

QwQ, developed by the Qwen team from China Alibaba group, is an experimental 32B model designed to enhance AI reasoning capabilities. It excels in analytical tasks, achieving strong results on benchmarks like GPQA (65.2%), MATH-500 (90.6%), and LiveCodeBench (50%), though it has limitations such as language mixing, recursive reasoning loops, and safety concerns. Built on Qwen2.5 with 32.5B parameters, QwQ features a 32,768 context length, making it particularly proficient in mathematics and programming. However, its reasoning abilities in common sense and nuanced language understanding are still evolving. Released under Apache 2.0 on Hugging Face, QwQ reflects a model in development, focused on deep, reflective problem-solving, yet requires refinement in certain areas.

The Qwen team, responsible for QwQ's creation, has crafted a model that embodies a philosophical approach to AI, emphasizing the importance of questioning and introspection. While still a work in progress, QwQ represents a step forward in AI reasoning with its potential to grow in sophistication over time.

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OpenAI Cookbook - OpenAI API examples and guides

The OpenAI Cookbook is a repository that provides example code and guides to help users accomplish common tasks using the OpenAI API. It offers practical solutions for integrating OpenAI models into projects, with most examples written in Python. Users will need an OpenAI account and an associated API key to run these examples. The cookbook provides detailed instructions on how to set up the API key, including creating an environment variable or using an .env file in development environments like Visual Studio Code. The examples in the cookbook cover a range of topics and can be applied to various programming languages, making it a valuable resource for developers working with OpenAI's API. Additionally, the cookbook links to related tools, guides, and courses for further learning.

Link to examples