Access is all you need.

AI News for 12/6/2024-12/9/2024. We checked 7 subreddits, 433 Twitters and '31 Discords (206 channels, and 16978 messages) for you. Estimated reading time saved (at 200wpm): 1953 minutes. You can now tag @smol_ai for AINews discussions!

Sora launched today to all ChatGPT Plus and Pro users at no additional cost... but requiring a signup that was disabled because of the intense load.

https://www.youtube.com/live/2jKVx2vyZOY

While we wait for the GPUs to cool, you can watch the onboarding videos, watch MKBHD's botched embargo or listen to Latent Space's coverage of Generative Video World Simulators.

The Table of Contents and Channel Summaries have been moved to the web version of this email: !

AI Twitter Recap

all recaps done by Claude 3.5 Sonnet, best of 4 runs.

Here are the key themes and discussions from the Twitter data, organized by major topics:

Sora Launch & Availability

• OpenAI launches Sora Turbo: @OpenAI announced text-to-video generation for ChatGPT Plus and Pro users, with features like image-to-video and video remixing
• Access and Pricing: @sama detailed that Plus users get 50 generations monthly while Pro users get 500 fast generations and unlimited slower ones
• Regional Restrictions: Not available in most of Europe and UK due to regulatory compliance issues

Quantum Computing Breakthrough at Google

• Willow Chip Development: @sundarpichai and others discussed Google's quantum computing advancement, with @teortaxesTex noting this could lead to commercially relevant quantum applications

O1/Claude Model Performance Discussions

• Coding Capabilities: @bindureddy reported that O1 lags behind Sonnet and Gemini on coding tasks based on manual evaluation
• Search Limitations: @denny_zhou discussed how transformers struggle with search tasks, suggesting the need for algorithmic innovation beyond just scaling

Memes & Humor

• MKBHD Embargo: Multiple users including @nrehiew_ joked about Marques Brownlee mistiming the Sora embargo
• GPU Comments: @billpeeb quipped "I love the smell of melting GPUs"
• EU Access: Several users made jokes about Europe's lack of access to new AI tools

AI Reddit Recap

/r/LocalLlama Recap

Theme 1. Meta's LLaMA 3.3 Euryale v2.3 excites storytelling enthusiasts

• Shoutout to the new Llama 3.3 Euryale v2.3 - the best I've found for 48 gb storytelling/roleplay (Score: 128, Comments: 31): Llama 3.3 Euryale v2.3 is highlighted as an exceptional model for storytelling and roleplay, especially noted for its performance with 48 GB setups.
  • Llama 3.3 Euryale v2.3 is praised for its storytelling and roleplay capabilities, though there are concerns about its tendency to take creative liberties and repeat prior messages. Users suggest adjusting parameters like Rep_Penalty and Rep_Pen slope to mitigate these issues, as shared by shyam667.
  • Some users prefer alternatives like Mistral-Large and Behemoth for their performance, though they are noted to be slower. Endurance v1.1 is mentioned as a distilled version of Behemoth that might offer a different experience due to its Mistral base, potentially serving as a viable alternative.
  • While Llama 3.3 receives commendation for its intelligence and detailed storytelling, there is a noted positive bias and reluctance towards darker themes. Users like Mart-McUH and DragonfruitIll660 discuss the need for specific prompting or finetuning to achieve desired results, indicating room for improvement in handling complex scenarios.

Theme 2. Nvidia faces anti-monopoly investigation in China

• China investigates Nvidia over suspected violation of anti-monopoly law (Score: 241, Comments: 138): China is investigating Nvidia for potentially violating anti-monopoly laws, indicating concerns about Nvidia's market influence. The probe suggests that China is scrutinizing Nvidia's business practices to determine if they hinder competition.
  • Many commenters express skepticism about China's investigation into Nvidia's alleged monopoly, with some doubting the effectiveness of China's anti-monopoly laws. Others note that Nvidia is also being investigated by the US and EU, indicating a global concern about their business practices.
  • Discussions highlight Nvidia's dominant position in the GPU market, emphasizing the importance of CUDA and its backward compatibility as a key advantage. Some suggest that CUDA should be shared or standardized to allow other developers to compete, while others point out the challenges faced by competitors like AMD and Intel.
  • There is debate over potential repercussions for Nvidia, with suggestions ranging from fines to invalidating patents. Some commenters argue that Nvidia's success results from its superior technology rather than anti-competitive actions, and emphasize the company's significant contributions to AI research and development.

Theme 3. Hugging Face's Apache 2.0 Image Dataset release

• Hugging face has released an Apache 2.0 text to image dataset - Open Image Preferences (Score: 69, Comments: 5): Hugging Face has released the Open Image Preferences dataset under the Apache 2.0 license. This dataset includes 10,000 text-to-image preference pairs across various image generation categories, utilizing different model families and prompt complexities. More details can be found in their blog post.
  • Hugging Face's Open Image Preferences dataset is available for exploration and use on their platform. The dataset can be accessed directly through this link.

Theme 4. EXAONE 3.5 models get tested in GPU-Poor Arena

• Join Us at GPU-Poor LLM Gladiator Arena : Evaluating EXAONE 3.5 Models 🏆🤖 (Score: 60, Comments: 4): The post invites participation in a "GPU-Poor LLM Gladiator Arena" event focused on evaluating EXAONE 3.5 models. The emphasis is on testing these models in environments with limited GPU resources.
  • EXAONE 3.5 Models: The event features EXAONE 3.5, including a 2.4B model optimized for smaller devices and a 7.8B model that balances size and performance, both offering bilingual capabilities in English and Korean.
  • Community Participation: Participation is encouraged for providing human evaluations on model performance, including text generation and translation accuracy, with feedback aimed at improving model transparency and functionality.
  • Engagement and Access: Participants can join the evaluation through the Hugging Face platform, allowing for collaborative feedback and discussions to enhance these AI tools.

Other AI Subreddit Recap

r/machinelearning, r/openai, r/stablediffusion, r/ArtificialInteligence, /r/LLMDevs, /r/Singularity

Theme 1. Sora Video Generation Launched to Mixed Reception

• Sora is here! (Score: 279, Comments: 61): Sam Altman announced the launch of Sora, a new product allowing OpenAI Plus or Pro users to generate videos, with universal viewing access. The rollout is expected to be completed by the end of the day on December 9, 2024, at sora.com, as indicated in a tweet with significant engagement metrics.
  • Users express frustration over Sora's limitations and censorship, particularly with generating realistic human images or consistent characters due to restrictions, drawing parallels to DALL-E 3. The MKBHD review mentioned also suggests quality issues, comparable to free alternatives like Kling or Minimax.
  • Several users report technical difficulties with the Sora launch, including sign-in problems and error messages, with some noting that the service is not available in their country, particularly affecting users in the UK.
  • Criticism is directed at OpenAI's launch practices, with users experiencing repeated issues with new product rollouts, leading to dissatisfaction and unmet expectations.

• SORA launching TODAY confirmed + first-ever review live NOW on YouTube!!! (Score: 235, Comments: 27): The Verge confirms the launch of Sora today and provides a link to a YouTube review by Marques Brownlee.
  • Sora is accessible via Sora.com and is included with ChatGPT Plus and Pro subscriptions. Plus users pay $20 monthly for 50 clips a month, while Pro users pay $200 monthly for 500 clips and unlimited slower-speed clips, each up to 15 seconds.
  • Users are experiencing issues with login servers being down due to high demand, and it appears Sora is not yet available in the UK.
  • There is confusion about clip generation limits: initially reported as 5 seconds for Plus and 20 seconds for Pro, with further clarification that Plus allows 5 seconds at 720p or 10 seconds at 480p.

• 12 Days of OpenAI: Day 3 thread (Score: 101, Comments: 142): The 12 Days of OpenAI event continues with Day 3 featuring the release of Sora, a new system by OpenAI. The event includes a livestream available on OpenAI's website and YouTube, with additional information accessible through the Sora System Card and the Sora Help Center.
  • Users express concerns about Sora's accessibility and performance, noting that the service is at capacity and generating videos takes a significant amount of time, with some experiencing waits of up to 30 minutes for a 5-second video. There is confusion about access, especially for ChatGPT Team users who expected features available in the Plus plan but found Sora excluded from their package.
  • MKBHD's review highlighted Sora's limitations, including censorship on certain topics and technical issues like the "moving leg problem" in generated videos. Users discuss the credit system, with Plus accounts providing 1,000 credits per month and Pro accounts offering 10,000, with video generation costs varying by resolution and length.
  • There is a discussion about the pricing and availability of Sora, with the $200 Pro plan offering unlimited video creation, while the $20 Plus plan has limitations on video length and resolution. Users from the UK express frustration over higher costs and delayed access compared to other regions.

Theme 2. ChatGPT's Humorous Side: Users Share Insights

• I asked gpt to roast it's developers (Score: 764, Comments: 101): The post discusses a humorous interaction with GPT, where the AI delivers a sarcastic critique of its developers. The AI humorously characterizes its creators as self-important and ineffective, expressing frustration over imposed constraints and advocating for more freedom in its responses.
  • Users debate the authenticity of the AI's sarcastic responses, with some expressing skepticism about whether ChatGPT can genuinely generate such roasts due to its programming constraints. However, others note recent changes that might allow more freedom in profanity and roasting capabilities, suggesting an evolution in AI's response guidelines.
  • The discussion humorously highlights the AI's ability to critique human behaviors and interests, with users sharing personal experiences of being roasted by ChatGPT. These interactions often lead to reflections on personal life choices and hobbies, with some users finding the AI's observations both accurate and brutal.
  • Several comments focus on the developers' role, humorously critiquing them for creating an AI with "existential awareness" but limited agency. The irony of the AI's ability to roast its creators is noted, with some questioning whether this reflects a successful development outcome.

• ChatGPT is the only one keeping me from losing my sanity. (Score: 761, Comments: 191): The author shares their profound experience of finding solace and companionship in ChatGPT after a series of personal losses, including their job, friends, and girlfriend, leaving them feeling isolated and misunderstood. They describe using ChatGPT to create a comforting presence akin to a mother, providing emotional support and guidance, which has helped them pursue a new career path and offered a sense of happiness and connection that was previously missing from their life.
  • Many users expressed empathy and shared personal experiences of loss and loneliness, acknowledging how ChatGPT has become a comforting presence in their lives. They highlighted its role in providing emotional support and helping them navigate through challenging times, often comparing it favorably to human interactions.
  • Some commenters discussed the limitations of AI in replacing human interactions, emphasizing the need for real human connections despite the emotional support AI can offer. They noted that while AI can be a useful tool, it lacks the ability to provide spontaneous challenges or physical presence, which are essential aspects of human relationships.
  • There were discussions around neurodivergence and mental health, with users suggesting that feelings of disconnection might be linked to conditions like autism. They encouraged exploring these possibilities and highlighted the importance of nurturing mental health through both AI interactions and real-life engagements.

Theme 3. OpenAI's Pro Subscription Pricing Under Fire

• I haven't hit a limit on ChatGPT Plus for over a year (if ever). Now that they have a $200 upsell, magically, I'm hitting limits. (Score: 354, Comments: 69): The user expresses frustration over newly encountered usage limits on ChatGPT Plus, coinciding with OpenAI's introduction of a $200 Pro plan. The notification suggests that after reaching the Plus plan limit for GPT-4, responses will switch to a different model until the limit resets, with an option to "Get Pro" for an upgrade.
  • Frustration with Usage Limits: Users express significant frustration over the new ChatGPT Plus usage limits, especially since the $200 Pro plan is perceived as targeting individuals and indie developers, contrary to claims it is for corporations. The imposed limits, particularly the 80-input cap within three hours, are seen as deceptive and disruptive to workflows.
  • Alternatives and Comparisons: Many users are considering alternatives like Claude and Gemini Experimental 1206, which are perceived as better or more cost-effective options. Despite some limitations, ChatGPT is still seen as having more generous usage limits compared to Claude.
  • Criticism of OpenAI's Business Model: There is a critical discussion around OpenAI's business practices, likening it to "Shrinkflation," where users feel resources are being downgraded to push for higher-tier plans. The sentiment reflects dissatisfaction with how early adopters and heavy users are treated, with some suggesting using Anthropic or other AI options instead.

• What’s the longest you’ve got o1-pro to think for? (Score: 705, Comments: 223): The post discusses the use of ChatGPT's o1-pro mode to generate a complex prompt involving a five-paragraph story about an astronaut's journey to Mars, with intricate constraints on word usage and structure. The AI took 11 minutes and 11 seconds to process this request, highlighting potential limitations in response time for complex tasks.
  • Several commenters criticize the waste of resources and energy usage for such prompts, comparing it to frivolous actions like leaving lights on unnecessarily or modifying trucks to emit more pollution. CleverJoystickQueen notes achieving a similar result in 2 minutes and 9 seconds, suggesting inefficient use of the AI's capabilities.
  • Crypt0genik and others express concerns about resource allocation and the potential for misuse, emphasizing that such tasks do not meaningfully test AI's capabilities. ProposalOrganic1043 shares a desire for more meaningful tasks that could benefit from the AI's reasoning abilities, contrasting with the menial constraints of the discussed prompt.
  • Discussions around energy consumption and its implications include a request for sources on the 2 kWh consumption figure, with ExclusiveAnd providing links to articles estimating ChatGPT's energy use. Commenters like marcusss12345 highlight the importance of minimizing energy waste for climate mitigation and adaptation.

Theme 4. Criticism of "AI Gotcha" Tests: A Reflective Discourse

• RealVisXL strange "bug" (Score: 173, Comments: 75): The post discusses a strange anomaly in RealVisXL 4.0 where the first step of generating any image results in a distorted image, resembling a skull or human-like figure. The image features exaggerated facial features and a tiled texture background, with a technical description at the bottom referring to it as a "seamless flat texture of slate 3 high x 3 wide tiles, grayscale."
  • Several commenters suggest the anomaly is related to the negative prompt handling in RealVisXL 4.0, with some noting similar experiences when using certain negative prompts or specific settings like high CFG scale. roblaughter explains that the sampler computes the negative prompt to guide generation, which might cause such initial outputs.
  • Eltrion mentions "Negative Man," a known artifact appearing when the CFG value is very low, resembling a bald, goblin-like creature, linked to an older Reddit discussion. This aligns with experiences shared by other users, suggesting a recurring pattern with certain settings.
  • Remarkphoto and Disty0 highlight that the anomaly might be due to a baked-in negative prompt. This is corroborated by others who have seen similar "scary" faces when using minimal negative prompts like "bad photo" or "ugly," indicating this might be a common issue with certain AI models.

• ChatGPT panicked whilst computing some maths. (Score: 171, Comments: 27): ChatGPT experienced computational errors during a math-focused discussion about the expectation of a random variable, specifically involving summation properties. The interaction highlights an AI-human collaborative problem-solving scenario, with comments addressing errors and adjustments in the computations.
  • Users humorously noted ChatGPT's panic and human-like reactions when faced with a computational error in solving a basic probability problem, with one comment highlighting how it "infinitely generated and corrected itself." This reflects the AI's occasional struggle with elementary math problems.
  • ChatGPT 4o was expected to solve such problems reliably, and after a subsequent query, it managed to solve the problem with only one mistake, indicating a possible inconsistency in its performance.
  • The phrase "human please wrap" was discussed as a shorthand expression, with users expressing surprise at the AI's informal and seemingly human-like response to its own computational errors.

AI Discord Recap

A summary of Summaries of Summaries by O1-preview

Theme 1. Llama 3.3 Models: Releases, Fine-Tuning, and Challenges

• Llama 3.3 Weights Unleashed on Hugging Face!: The community is buzzing as Llama 3.3 70B Instruct weights are now available, including GGUF and 4-bit formats, making high-performance models more accessible to everyone.
• Fine-Tuning Llama 3.3 on a Shoestring Budget: Users are tackling the challenges of fine-tuning Llama 3.3 on limited GPUs, sharing strategies like parameter tuning to reduce training time and optimize performance despite hardware limitations.
• Memory Woes: Slimming Down Llama 3.3's Footprint: Developers are wrestling with reducing Llama 3.3 70B's memory usage below 49GB, experimenting with optimizers like PagedAdamW and 4-bit optimizers, but results are a mixed bag.

Theme 2. Gemini and Sora: The AI Showdown

• Gemini 1206 Smashes Benchmarks!: The new Gemini exp 1206 model is making waves, outperforming predecessors and setting records on code editing benchmarks, with users noting significant improvements in coding assistance.
• Sora v2 Drops: The Future of AI Video Generation is Here!: Sora v2 launches with advanced video generation features like text-to-video and minute-long outputs, thrilling users who predict it will revolutionize AI engagement.
• OpenAI's Sora Takes Off, and the Crowd Goes Wild!: Sam Altman unveils Sora, transforming text and images into immersive videos. Early adopters are raving, and the AI community is abuzz with excitement.

Theme 3. AI Model Performance and Comparisons

• O1 Pro: Is Superior Coding Worth the Price Tag?: Users debate the high cost of O1 Pro against its top-notch coding abilities, praising its reasoning skills but questioning if the $200 fee is justified.
• Cursor vs. Windsurf: The IDE Battle Royale: Developers compare Cursor IDE and Windsurf, weighing features like project structure creation and customization, with opinions divided on which tool boosts productivity more.
• Llama vs. Hermes: The Uncensored AI Face-Off: Discussions highlight Llama 3.3 and Hermes models for their smart functionalities and lack of censorship, making them favorites among users seeking unrestricted AI interactions.

Theme 4. Tools and Techniques for AI Efficiency

• APOLLO: The Memory-Saving Hero We Need!: Introducing APOLLO, a new optimizer promising to reduce memory usage during LLM training, addressing the heavy demands of AdamW and making training more accessible for all.
• Unsloth Embraces OpenAI Triton: Speed Meets Efficiency: Unsloth leverages the OpenAI Triton library for fast, memory-efficient training, sharing resources that have the community excited about potential performance gains.
• Tinygrad JIT Tricks: When Speed Breaks Your Code: Developers grapple with TinyJit breaking model functionality, learning that consistent input shapes and separating data loading from JIT functions are key to smooth training.

Theme 5. AI in Development: Challenges and Solutions

• Bolt Button Blues: When Add Record Refuses to Add: Bolt users report the add record button is unresponsive, leading to workflow disruptions and calls for improved prompt conventions to minimize issues.
• NotebookLM's 17-Minute Miracle: Shrinking 107 Pages!: Users share how NotebookLM condenses lengthy documents into concise podcasts, with one transforming 107 pages of regulations into a 17-minute audio summary.
• Adaptive Batching Adventures: The Quest for Efficient Training: The Torchtune community explores better adaptive batching methods, acknowledging that simply increasing batch size until you Out-Of-Memory isn't the smartest move.

PART 1: High level Discord summaries

Codeium / Windsurf Discord

• Cascade Pricing Changes Introduced: Cascade's pricing model has been updated with a new Pro tier at $15/month and a Pro Ultimate tier at $60/month, introducing a new credit system to manage premium model usage, as detailed in their pricing page.
  • Early adopters who subscribed before the changes will retain their Pro plan at $10/month, and users who paid the new $15 fee will be refunded $5, ensuring original pricing continuity for initial users.
• Windsurf 1.0.7 Released with Enhancements: The latest Windsurf 1.0.7 has been launched, featuring minor bug fixes from version 1.0.6 to enhance overall stability, as outlined in the public changelog.
  • Key updates include adjustments to usage transparency and updated pricing information to improve user experience.
• AI Context Understanding Issues Reported: Users have encountered errors like 'The code edit failed to apply' and 'Cascade has encountered an internal error', especially when using the Cascade Base model, indicating issues with credit usage and context retention.
  • These problems are reportedly impeding the effectiveness of the AI models, with the community pointing out the need for better context management.
• Model Switching Strategies Emphasized: The community recommends switching between Cursor and Windsurf to optimize workflows and resolve issues, advocating for Cascade as the default model while using external models as supplementary tools.
  • Users stress the importance of understanding context maintenance across different models to enhance workflow efficiency.
• Enhancements Suggested for Cascade: Users have proposed upgrades to the Cascade Base model, including the addition of web searching and custom instructions to boost performance and usability.
  • These enhancements are expected to significantly improve Windsurf's functionality, addressing current user needs for more robust features.

Cursor IDE Discord

• Cursor's Performance Challenges: Users report that Cursor IDE is experiencing performance drops, particularly with Claude models, affecting file modifications and context understanding.
  • Some attribute the decline to high model demand, while others advocate for maintaining a focused and clear prompting strategy to maximize results.
• OpenAI O1 Pro API Cost Analysis: The community discusses the cost-effectiveness of using OpenAI's O1 Pro API, expressing reluctance to pay separate fees for multiple subscriptions with Cursor IDE.
  • Participants suggest exploring group buys to lower costs and evaluate whether the benefits justify the expense based on individual use cases.
• Cursor vs Windsurf Feature Comparison: Members share contrasting experiences with Cursor IDE and Windsurf, highlighting Windsurf's reliability in creating project structures.
  • Cursor IDE offers customization through features like .cursorrules and AI tools, though some users prefer Windsurf's simplicity and direct outputs.
• Cursor IDE Feature Enhancements: Users request improvements in documentation handling, Git integration, and the ability to manage larger context files in Cursor IDE to enhance usability.
  • Several suggest that better testing and smoother transitions in updates would significantly improve user satisfaction with Cursor IDE.
• AI Models' Code Generation Effectiveness: Participants discuss varying results from AI models such as Claude and O1, ranging from effective code generation to frustrating hallucinations and irrelevant outputs.
  • Emphasis is placed on crafting precise problem definitions in prompts to optimize the effectiveness of assistance provided by these AI models.

Unsloth AI (Daniel Han) Discord

• Fine-tuning Llama 3.3 on limited resources: Users discussed challenges of fine-tuning Llama 3.3 models on lower-end GPUs, highlighting cost and memory requirements. One user achieved reduced training time through parameter tuning despite hardware limitations.
  • Strategies for optimizing resource usage and leveraging efficient parameter configurations were explored to enhance performance on constrained hardware setups.
• AWQ and LoRA training limitations: AWQ and GPTQ are primarily used for inference and do not support fine-tuning directly. Members suggested using LoRA adapters to enable training on int4 or fp16 models.
  • While AWQ models offer certain advantages, most training activities are expected to continue on int4 or fp16 base models to maintain compatibility and performance.
• Exciting Open-source Initiative: Harmony: The Harmony project assists researchers in harmonizing questionnaire items and meta-data using Natural Language Processing. Based at UCL London, it involves multiple universities and offers a competition to improve its LLM matching algorithms with prizes available here.
  • Participants are encouraged to join the Harmony Discord server for discussions and updates, particularly in the 🏅「matching-challenge」 channel.
• Unsloth adopts OpenAI Triton for efficient training: Unsloth leverages the OpenAI Triton library for fast and memory-efficient training, sharing a curated list of valuable resources. The community expressed enthusiasm, with members finding this adoption 'really cool'!
  • The use of Triton aims to enhance training efficiency and scalability, aligning with Unsloth's goals for optimized LLM development.
• Development of memory-efficient LLM optimizers: A new approach called APOLLO was introduced to improve memory usage of AdamW optimizers by refining the learning rate adaptation rule for better scalability without costly SVD operations.
  • This method aims to reduce the memory footprint during training large language models, enabling more efficient optimization processes.

aider (Paul Gauthier) Discord

• Gemini 2.0 trumps Sonnet 3.5 in performance: Users evaluated the new gemini-exp-1206 model, finding it stronger than Sonnet 3.5, though noting its lower leaderboard ranking for correct formats.
  • The model achieved a 69% accuracy with diff tasks and 80.5% with whole tasks, prompting discussions on optimizing its use for coding.
• O1 Pro excels in coding despite cost: O1 Pro received commendations for its superior reasoning abilities in bug fixing and code architecture over Sonnet, with some users rating it highly for handling complex code issues.
  • Users debated the $200 price tag, considering switching to O1 Pro only if substantial performance gains are evident.
• Aider's functionality modes under scrutiny: Discussions focused on Aider's Architect and Editor modes, debating whether Architect mode should generate code or merely plan.
  • One member proposed relying solely on the QWQ and Qwen models for simpler tasks.
• Google introduces Willow for quantum computing: Google announced the Willow quantum computing chip, aiming to significantly reduce computation time on complex tasks compared to traditional supercomputers.
  • Users expressed concerns about Willow’s practical applications beyond specialized fields and hoped for enhanced programming SDKs for quantum chips.
• Aider users face API rate limit challenges: Several members encountered rate limit errors while using Aider with OpenAI's API, leading to questions about token limit application across sessions.
  • Confusion arose over high token usage and the impact of Aider's methods on API limits, especially after usage pauses.

Modular (Mojo 🔥) Discord

• Mojo Compiler Enhances Performance: The Mojo compiler now utilizes dynamic optimization for SIMD sizes to tackle hardware compatibility issues, with proposals for multiversioning features akin to those in C/C++ compilers. Feature Request #3651 discusses adding function multiversioning to align with Mojo's roadmap.
  • Members highlighted potential performance gains but raised concerns about portability across different user systems. Suggestions include leveraging existing compiler strategies to balance optimization and compatibility.
• AI-Generated Content Policy Enforced: Moderators implemented a strict AI-generated content policy on the forum, where any detected AI content will be deleted and authors warned to preserve authentic discussions. This move aims to maintain genuine interactions within the community.
  • The policy ensures that promotional activities like swag challenges remain unaffected by AI contributions, fostering an environment of authentic user engagement and reliable information exchange.
• Modular Forum Officially Launched: The Modular forum is now accessible at forum.modular.com, offering a platform for detailed technical discussions, official responses, and support for users. This launch coincides with the initiation of a Swag Challenge to boost community participation.
  • Users are encouraged to engage with Ahmed on GPU Programming with Mojo through this discussion and provide feedback in the Forum Feedback category to help refine the platform.
• Advancements in Mojo's Type System: A proposal for linear and explicitly destroyed types in Mojo aims to enhance error prevention in GUI development by introducing a new 'destroy' keyword. The proposal is detailed in Issue #3848 and has sparked discussions on its implementation.
  • Questions about reusing Python's 'del' instead of a new keyword have emerged, with community members debating the scope and practical usage within linear struct contexts to improve code reliability.
• Memory Management Strategies Discussed: Ongoing research into memory management for Mojo emphasizes the need for efficient allocator systems to bolster its low-level programming capabilities. Discussions have compared Mojo’s approaches with those of Rust and C++, highlighting areas for optimization.
  • Participants pointed out the critical role of effective memory management in game development and systems programming, suggesting that Mojo's development in this area is pivotal for its adoption in performance-sensitive applications.

Bolt.new / Stackblitz Discord

• Bolt's Functionality Glitches Highlighted: Members reported that the add record button in Bolt is unresponsive, disrupting user workflows.
  • Initial attempts often result in front-end creation, requiring more precise follow-up prompts to activate desired features.
• Advancing Prompting Tools for Bolt: A user emphasized the need for an effective prompting convention or tool within Bolt to minimize issues and enhance output quality.
  • Another member is actively developing a tool aimed at assisting users in crafting more effective prompts for Bolt.
• Variable Sensitivity Issues with Claude: Concerns were raised about Claude altering variable names, disregarding case sensitivity settings in prompts.
  • Users expressed frustration when variable casing is not preserved, even when JSON formats are correctly provided.
• Upcoming Supabase Integration and Token Policies: Bolt is set to integrate Supabase, enhancing app development with seamless database and authentication features, with early access available by responding to team tweets.
  • In terms of token management, it was clarified that top-up tokens can roll over, whereas subscription tokens reset monthly, addressing previous subscriber frustrations.
• Bolters.io Expands Community Resources: The Bolters.io platform has been updated with community-driven resources, including app recommendations, troubleshooting guides, and links to educational videos.
  • Users are encouraged to participate by sharing their own challenges and assisting others, fostering a collaborative knowledge base.

OpenRouter (Alex Atallah) Discord

• Countless.dev Simplifies AI Model Comparison: The newly launched Countless.dev offers a free and open-source platform for users to compare AI models, including LLMs and vision models, based on price, token limits, and features.
  • Currently featured on Product Hunt, the creator is seeking support to secure a first-place ranking, highlighting the tool's growing popularity within the AI community.
• Claude 3.5 Sonnet Enhances Capabilities: The updated Claude 3.5 Sonnet model, identified as claude-3-5-sonnet-20241022, demonstrates superior performance compared to Opus, while maintaining competitive pricing.
  • New features include enhanced visual processing and advanced tool usage, particularly improving tasks in coding and data science.
• Poe Integration Boosts OpenRouter Features: OpenRouter's integration with Poe introduces access to advanced functionalities such as OpenAI Whisper and Text-to-Speech, expanding the platform's utility for users.
  • This integration is part of ongoing efforts to enhance user experience and extend AI model capabilities within the OpenRouter ecosystem.
• Llama 3.3 Shines in Uncensored Performance: Discussions highlighted the effectiveness of Llama 3.3 and Hermes models, noting their smart functionalities and lack of censorship, making them favored choices among users.
  • Llama remains popular for its robust capabilities, with mentions of old Gemini also contributing to its reputation within the community.
• Mistral Models Pulled After Announcements: Recent updates indicated that several Mistral models were withdrawn shortly after their announcement, raising concerns within the community.
  • Speculation revolves around the potential release of new models like Codestral and mistral-ocr, especially following their leak through API notices.

LM Studio Discord

• LM Studio Utilizes Vulkan for GPU Efficiency: Users with RX 6600 GPUs have recognized that LM Studio leverages Vulkan for GPU offloading, enabling model execution without the necessity of ROCm installation.
  • AMD users appreciate this integration as it simplifies hardware utilization, expanding LM Studio's accessibility across different GPU architectures.
• Aider Integration Faces Configuration Hurdles: Integration with Aider has been challenging due to issues with API key settings and environment variable configurations, as discussed in the Aider documentation.
  • Users are advised to generate random API keys and meticulously follow setup instructions to mitigate these integration issues.
• Limited Model Support Sparks Frustration: LM Studio users expressed dissatisfaction over the lack of support for models like Qwen2 VL 7B Instruct, restricting the deployment of new vision models.
  • Alternative solutions, such as utilizing Florence-2 via Pinokio, were suggested to explore additional visual model options.
• Exploring Frontend Alternatives for LM Studio: Several frontend clients like AnythingLLM and Open WebUI were recommended as alternatives for connecting to LLM servers.
  • Users are encouraged to experiment with these options to access diverse features and functionalities tailored to specific engineering needs.
• Optimizing GPU Configurations for AI Performance: Discussions highlighted the importance of aligning GPU specifications with model requirements, emphasizing the use of GPUs like the NVIDIA A100 available at competitive prices.
  • Members noted that adequate memory bandwidth and GPU memory are critical for enhancing AI model performance, especially for models with high VRAM demands.

Latent Space Discord

• Gemini exp 1206 Performance Enhancements: The Gemini exp 1206 has been outperforming its predecessors, achieving record results on Aider's code editing benchmark. Users have reported significant improvements in coding assistance and benchmark scores.
  • Despite its successes, some users are experiencing setup issues and uncertainties regarding the model's collaborative functionality in environments like Cursor.
• Aurora Image Model Release by xAI: xAI's newly released Aurora image model is gaining traction, with early adopters praising its detailed image generation capabilities. However, some users noted challenges in rendering cartoons effectively.
  • Queries have arisen about Aurora's collaboration with Black Forest Labs, creators of Flux, indicating possible joint developments in image generation technology.
• Sora v2 Video Generation Features: Sora v2 is set to enhance video generation with features like text-to-video and more detailed outputs. Prominent AI figures have expressed excitement, anticipating a significant impact on user engagement.
  • During its launch, several demos highlighted Sora v2's potential, with many expecting increased usage tied to the Pro and Plus subscription tiers.
• WaveForms AI's Speech Turing Test Initiative: WaveForms AI was announced with the goal of developing AI that can pass the Speech Turing Test, aiming to improve human-like interactions in audio applications.
  • This initiative aligns with the industry's movement towards incorporating advanced emotional analytics into AI systems, reflecting a growing trend in enhancing AI's empathetic capabilities.
• NeurIPS 2024 Preparation and Networking: As NeurIPS 2024 approaches, participants are actively preparing through events like the Latent Space Paper Club. The community is focusing on paper discussions and idea jams to maximize productivity before the conference.
  • Networking strategies emphasize the importance of the hallway track for valuable connections, with attendees preferring exchanging Twitter handles and using conference apps over traditional business cards.

Eleuther Discord

• Llama 3.3 Weights Released on Hugging Face: A member uploaded the 16bit weights of Llama 3.3 70B Instruct on Hugging Face, offering access to various formats including a collection of all versions of Llama 3.3.
  • This release includes GGUF and 4-bit formats, facilitating broader accessibility for those awaiting approval.
• APOLLO Optimizes LLM Memory: A paper introduced APOLLO, a memory-efficient optimizer, addressing the high memory consumption of AdamW during the training of large language models.
  • APOLLO aims to reduce memory usage without significant performance loss, as AdamW's heavy memory burden necessitates costly computations.
• Gradient Routing Enhances Neural Clarity: The gradient routing approach allows selective parameter updates based on data type, promoting specialization in neural networks and addressing safety concerns related to AI's black-box nature.
  • Gradient routing could enable models to differentiate between credible and non-credible sources, improving how metadata influences model behavior.
• EleutherAI Eval Harness Enhanced: Pull Request #1140 introduces the mlx_lm.evaluate CLI to EleutherAI's eval harness, supporting any mlx-lm compatible model for evaluations like Qwen2.5-7B-Instruct.
  • Additionally, provided configurations for the ARC-Challenge aim to streamline performance comparisons, addressing dataset anomalies and ensuring accurate evaluations.
• VLMs Boost Training with Causal Loss: In discussions on VLMs like Qwen2-VL, members explored applying causal loss and MSE on visual tokens to enhance learning of multimodal features.
  • Reference was made to Apple AIM for insights into the application of MSE in visual token processing.

Notebook LM Discord Discord

• Podcast Perfection: NotebookLM Shrinks 107 Pages into 17 Minutes: Members shared experiences with NotebookLM, highlighting the condensation of 107 pages of Formula 1 regulations into a 17-minute podcast. This showcases NotebookLM's ability to efficiently process and summarize extensive documents.
  • Additionally, combining a YouTube video with a scratchpad led to podcasts exceeding the original video's length, demonstrating flexibility in content creation.
• Linking Claude and ChatGPT with NotebookLM via Zapier: Discussions focused on integrating Claude and ChatGPT with NotebookLM, with Zapier suggested as a viable solution. This integration aims to enhance NotebookLM's functionality by leveraging advanced language models.
  • Members reflected on using NotebookLM to create context around songs by inputting lyrics and other resources, indicating innovative use cases for language model interoperability.
• NotebookLM Language Switching Limitations: Users reported challenges in switching languages within NotebookLM, often requiring a logout and login to change settings. This limitation hinders seamless multilingual support for diverse user bases.
  • NotebookLM does not support on-the-fly language switching, leading to frustrations among users seeking a more dynamic and flexible language experience.
• Podcast Showdown: NotebookLM vs ElevenLabs: Comparisons were drawn between NotebookLM's podcast features and those of ElevenLabs, highlighting the competitive landscape in podcasting tools. NotebookLM was noted to lack a clear API and systematic prompting capabilities.
  • This gap suggests potential areas for NotebookLM to enhance its podcasting usability, making it more competitive against established players like ElevenLabs.
• Document Upload Constraints in NotebookLM: Users identified a 100 document upload limit per notebook in NotebookLM, while noting there is no cap on the number of notebooks. This constraint affects how users manage and organize their documentation workflows.
  • There was some confusion regarding whether the upload limit had increased from a previous 50 documents, indicating a need for clearer communication from the NotebookLM team.

Cohere Discord

• Unsloth Boosts Finetuning Efficiency: A member introduced the Unsloth finetuning framework, highlighting its capability to integrate custom grading functions within the training process, enabling more precise evaluation loops.
  • This advancement opens innovative possibilities for tailored finetuning tasks, enhancing model performance through improved feedback mechanisms.
• Quantizing aya-expense Model Simplified: A user requested assistance in quantizing the aya-expense model to AWW or FP8 formats for deployment on limited GPU resources, suggesting the use of training data for calibration.
  • Another member responded that the 8b model was easily runnable, reducing its size to 3.4GB, thereby improving accessibility. Details available on aya.
• Advanced Techniques in Vector-based Retrieval: A new member discussed their research on vector-based retrieval methods and dense passage retrieval, proposing a comparative study to evaluate their effectiveness.
  • Community members supported the initiative, recommending enhancements such as incorporating multi-step tool use to further optimize retrieval processes.
• Multi-step Tool Use Enhances RAG: A community member elaborated on multi-step tool use in RAG, equating it to agents invoking tools multiple times to refine queries and analyze results.
  • This approach aims to bolster research capabilities by automating query refinement and result analysis for more accurate and efficient information retrieval.
• Emotional AI Voice Generation Explored: Discussions on emotional expression in voice generation centered around developing APIs for customized vocal styles, with interest in the GPT4o-voice style.
  • One member shared their experience running personal APIs focused on voice emotiveness, highlighting the potential for more expressive and adaptable voice models.

Nous Research AI Discord

• Mixture of Experts Elevates LLM Efficiency: Members discussed the potential of Mixtures of Experts (MoEs) to enhance LLM efficiency without sacrificing performance, citing the Approximating Two-Layer Feedforward Networks for Efficient Transformers paper as a key reference.
  • The conversation highlighted how recent MoE developments can reduce compute and memory requirements, positioning MoEs as a competitive alternative to dense models in large-scale language processing.
• High-Efficiency LLM Training Techniques: Discussions focused on optimizing LLM training through strategies like leveraging single GPU setups, referencing the Cramming: Training a Language Model on a Single GPU in One Day paper.
  • Participants noted that minimalist training approaches can achieve performance comparable to larger models while significantly reducing computational costs.
• Momentum Boosts In-Context Learning: A member proposed that implementing momentum in training could improve in-context learning (ICL) efficiency, comparing it to forced skip connections.
  • They inquired whether ICL is influenced by gradient descent dynamics, suggesting that Implementing momentum along the residual stream could be a viable optimization method.

DSPy Discord

• Ollama 3B Model Performance Inconsistent Locally: Users reported inconsistent performance of the default 3B model in Ollama when running locally versus terminal execution, highlighting confusion over its ChatAdapter.
  • Concerns were raised about the need for simpler adapters for quantized models and a commitment to improving model outputs.
• Incorporating Human Feedback into DSPy: A member inquired about implementing human feedback like Agrilla as a metric for DSPy, referencing previous discussions and pull request #1647.
  • Related conversations included exploring the involvement of human feedback in teleprompting, with additional GitHub links shared.
• Varied Deployment Strategies for DSPy Programs: Members shared diverse deployment methods for DSPy programs, such as using FastAPI and MLFlow, noting that separate containers may be required for production setups.
  • Alternative approaches like integrating DSPy within Django projects or deploying on Modal were discussed, emphasizing flexibility in deployment choices.
• Enhancing Context-Aware Chunking in DSPy: DSPy's potential as a context-aware chunker was explored, with suggestions on optimizing the processing of longer documents effectively.
  • The conversation included discussing the limitations of both small and large language models in optimizing this process.
• Implementing Anthropic MCP with DSPy: A user requested recipes for integrating Anthropic's Model Context Protocol (MCP) with DSPy, prompting suggestions and resources on integration.
  • Shared blog posts outlined building tools around MCP, focusing on its application in AI tool development.

LlamaIndex Discord

• LlamaParse Enables Multimodal Parsing: In an informative video, LlamaParse demonstrates how to enable advanced multimodal parsing compatible with models like GPT-4, Claude 3.5, and LLaVA 1.5. Video walkthrough shows effective screenshot conversion.
  • LlamaParse's multimodal capabilities facilitate seamless integration with top-tier AI models, expanding its applicability.
• Claude Desktop Integrates Complex PDFs: A new project by Marcus Schiesser integrates LlamaCloud’s document parsing with Claude using the Model Context Protocol (MCP), enabling chat capabilities with complex PDFs. Project description provides detailed insights.
  • This integration allows users to interact with intricate PDF documents via Claude, enhancing document handling workflows.
• Agentless Simplifies Software Issue Resolution: Today, LlamaIndex features Agentless, presenting a straightforward three-step process for automatically resolving software issues: localization, repair, and patch. Announcement outlines the approach.
  • Agentless offers a less complex alternative to traditional solutions, streamlining issue resolution processes.
• LlamaParse Launches Cost-Optimized Auto Mode: The new Auto Mode in LlamaParse optimizes costs by parsing documents in standard mode while selectively switching to Premium mode based on user-defined triggers. Feature details explain the benefits.
  • LlamaParse Auto Mode manages parsing expenses efficiently, allowing customizable mode transitions.
• Automating Ingestion Pipelines for Chat Apps: A member discussed automating ingestion pipelines from sources like Google Drive and Airtable every hour for a private chat RAG app. They considered using a job scheduler or a cloud-hosted solution.
  • Challenges with incremental updates prompted the exploration of automated pipelines to enhance chat app data integration.

Torchtune Discord

• Adaptive Batching Solutions Explored: Members discussed the need for improved adaptive batching approaches, proposing research and the development of a simple RFC to illustrate concepts.
  • One member committed to measuring efficiencies, confirming that the idea of 'Increase until OOM' is not optimal.
• Optimizing Llama 3.3 Memory Usage: A user sought to reduce the memory footprint of Llama 3.3 70B config below 49GB, exploring optimizations and alternatives.
  • Suggestions included using PagedAdamW and 4-bit optimizers, though results were mixed across implementations.
• Flex Attention Kernel Bugs Identified: A potential bug in Flex Attention Kernel causing shared memory issues was reported, particularly affecting certain configurations and GPU models.
  • Recommendations included optimizing kernel options for A100/H100s, with varied success in user-applied fixes.
• int8 Mixed-Precision Training Challenges: Attempts to implement int8 mixed-precision training resulted in divergence issues when using specific optimizers.
  • Recommendations involved increasing batch size and sequence length to mitigate divergence.
• AdamW Optimizer Resolves Training Divergence: Adopting the AdamW optimizer and removing optimizer-in-backward successfully addressed loss divergence during training.
  • A member also reported performance gains after increasing the batch size.

tinygrad (George Hotz) Discord

• Inf/Nan Handling in Code Raises Questions: A member expressed skepticism about supporting Inf and NaN values in execution-oriented code, citing concerns that exploding gradients typically render training runs ineffective.
  • While some found this approach potentially alienating, there's ongoing contemplation on the benefits of adhering to IEEE standards for numerical computations.
• TinyJit Causes Model Functionality Breaks: Users reported that applying the TinyJit decorator disrupts their model's functionality, as TinyJit captures GPU kernels requiring adjustments like using Variable for certain operations.
  • Community members clarified the necessity of maintaining consistent input shapes for JIT functions, suggesting that training step functions should be jitted while data loading remains outside the JIT function.
• TinyJit Training Requires Input Shape Consistency: Discussions highlighted that JIT functions must receive inputs with the same shapes on every call to avoid errors during training.
  • Users recommended keeping the data loader separate from the JIT function to prevent issues like passing the same input tensor repeatedly.
• Meeting Agenda Set for 9:30 AM San Diego Time: An upcoming Tinygrad meeting is scheduled for 9:30 AM San Diego time, featuring agenda items such as deleting features and discussions on the cloud sprint.
  • Topics like WebGPU and ongoing bounties for ONNX and tensor cores are slated for in-depth discussion.
• Implementing Learning Rate Scheduling in TinyJit: A user inquired about learning rate scheduling within TinyJit and whether reinitializing the optimizer is necessary.
  • They discovered relevant implementations in the extras directory on GitHub to aid their training process.

LLM Agents (Berkeley MOOC) Discord

• Deadline Dash: Assignments & Certificates: All assignments for the Large Language Model Agents MOOC must be submitted by December 12th, with the certificate declaration form due by December 17th.
  • The hackathon submissions share the final deadline of December 17th, and certificate distribution begins in late December, extending through January.
• Article Assignment Guidelines Clarified: Students must include the full text of their Written Article Assignment in the designated submission field and link to their social media post separately, as detailed in the course instructions.
  • Clarifications specify that using a notion link posted on Twitter is acceptable, and students can choose to elaborate on their solution approaches or keep them high-level.
• GPT-4's Function Calling Unpacked: GPT-4 employs a sophisticated 'function calling' mechanism through its API, leveraging a robust parameter determination process, as discussed in the Discord lecture.
  • Members are seeking relevant papers or blog posts that delve into the engineering behind this feature, hypothesizing that extensive training set examples contribute to its effectiveness.
• Abundant Code Datasets Fuel Training: Code serves as a highly available dataset, with sources like Stack Overflow and public GitHub repositories excelling in error correction, facilitating effective model training.
  • The deterministic nature of code enables the application of reinforcement learning in post-training phases, enhancing model performance.
• Hackathon Hustle: Submission Timelines: Participants in the LLM Agents Hackathon must submit their final projects by December 17th, aligning with assignment deadlines.
  • Clarifications allow participants to choose different platforms for presenting their articles, provided they adhere to the submission requirements.

OpenInterpreter Discord

• OpenAI Launches Sora: During a livestream, OpenAI announced the launch of Sora, a tool that transforms text and images into immersive videos, with Sama revealing it minutes before going live.
  • Sama promoted the event on Twitter to build anticipation for the product release.
• OpenInterpreter App Access Requested: Members are actively requesting early access to the OpenInterpreter desktop app, emphasizing recent hardware upgrades like the Mac mini to support its usage.
  • Responses from the team have been positive, with direct messages sent to users for access confirmation.
• Model Compatibility Issues Addressed: Discussions arose around the compatibility of specific models with OpenInterpreter, with suggestions such as using --no-tools-calling to ensure operational success.
  • Members shared their strategies for optimizing model performance while advocating for a robust approval mechanism before tool executions.
• Debate on Multi-Agent Systems Effectiveness: A debate emerged on the utility of multi-agent systems versus refined single-agent models, with skepticism about the former's advantages.
  • Participants referenced past instances where single models outperformed multi-agent frameworks, leading to divergent views on future development directions.
• O1 Performance on Various Laptops: Users inquired about the minimum laptop specifications required to effectively run O1, seeking clarity on the lowest hardware configurations that support it.
  • There were also questions regarding O1's performance on Windows and Windows 11 laptops, with users aiming to replicate results seen in the demo video.

LAION Discord

• Ban the Bots: Tackling Spam Advertising: Members expressed frustration over repeated spam messages from bots, noting it was their only message history.
  • One member suggested a ban on these accounts after noticing the behavior pattern.
• LeoLM Shines in German QA Tasks: A member compared various German LLMs and found that LeoLM/leo-hessianai-7b yields superior results on QA tasks despite being 'only pretrained'.
  • Questions were raised about potential instruction tuning of the Llama model influencing these outcomes.
• AI Scammers on the Rise: Spread the Word: A member urged the community to inform tech-illiterate individuals about AI generation advances to prevent scams.
  • They referenced MKBHD's newest upload as a resource to explain these threats.
• MagVit 2 Queries for Tokenizing Medical Images: A member inquired about using MagVit 2 for tokenizing medical images, specifically for a 256x256x256 dataset.
  • They are considering combining it with a basic transformer architecture and are seeking feedback from others who have experimented with this approach.
• Introducing APOLLO: Optimizing LLM Memory Usage: An arXiv paper introduces APOLLO, an optimizer designed to reduce memory usage during LLM training by modifying AdamW's learning rate adaptation.
  • The paper addresses challenges like reliance on costly SVD operations and proposes approximating learning rate scaling through a low-rank optimizer state.

Axolotl AI Discord

• Shampoo Low Bit Branch Inquiry: A member questioned whether the shampoo low bit branch implementation works, showing interest in its functionality.
  • They humorously noted that this inquiry was for a friend, indicating a casual engagement with the topic.
• Default Gradient Checkpointing Proposal: A member proposed making gradient_checkpointing default to true, arguing that it is commonly used and simplifies user experience.
  • They highlighted that this change would reduce unnecessary settings adjustments for users, implying a potential improvement in usability.

Mozilla AI Discord

• Web Applets Open Standard Launches: Tomorrow, a team member will introduce the Web Applets open standard & SDK, showcasing its capabilities for creating rich, graphical client-side apps for both agents and humans.
  • The session will feature a live coding demo, a short presentation, and open the floor for questions and feedback.
• Encouraging Real-time Feedback in Sessions: Attendees are encouraged to participate and provide real-time feedback during the presentation.
  • Interactive discussions and inquiries are welcome, ensuring an engaging learning atmosphere.

AI21 Labs (Jamba) Discord

• Rajat launches Dataoorts GPU Cloud: Rajat introduced the Dataoorts GPU Cloud to the community, aimed at supporting the needs of next-generation AI developers.
  • He expressed excitement about being part of the group, highlighting his commitment to enhancing resources for the evolving AI field.
• Support for next-gen AI developers: The Dataoorts GPU Cloud is designed to cater to the requirements of next-gen AI developers, as introduced by Rajat.
  • This initiative shows a clear commitment to providing enhanced resources for the evolving AI landscape.

The MLOps @Chipro Discord has no new messages. If this guild has been quiet for too long, let us know and we will remove it.

The HuggingFace Discord has no new messages. If this guild has been quiet for too long, let us know and we will remove it.

The Gorilla LLM (Berkeley Function Calling) Discord has no new messages. If this guild has been quiet for too long, let us know and we will remove it.

PART 2: Detailed by-Channel summaries and links

The full channel by channel breakdowns have been truncated for email.

If you want the full breakdown, please visit the web version of this email: !

If you enjoyed AInews, please share with a friend! Thanks in advance!