The First AI Specialized for Fiction Writing: Sudowrite's launches Muse.
Sudowrite's launches Muse, which is a groundbreaking advancement in AI for fiction writing, tailored specifically to meet the needs of authors. This specialized AI model has been meticulously trained on a curated dataset with full author consent, focusing on crafting high-quality, literary prose that excels in scene construction, character development, and avoiding clichés.
@webthreeth
Sudowrite's launches Muse, which is a groundbreaking advancement in AI for fiction writing, tailored specifically to meet the needs of authors. This specialized AI model has been meticulously trained on a curated dataset with full author consent, focusing on crafting high-quality, literary prose that excels in scene construction, character development, and avoiding clichés.
@webthreeth
Web 3.0 Ethiopia - DeFi & AI
Manus AI: Pioneering the Era of the First General AI Agent Manus AI, a Chinese-based AI startup, is being hailed as the world’s first fully autonomous AI agent, designed to handle complex, real-world tasks independently—planning a trip to Japan, analyzing…
Waiting on the trial, but China might have just done it again. From what I saw in reviews. This is impressive as hell.
Web 3.0 Ethiopia - DeFi & AI
Manus AI ME-CFS report.pdf
I just got an access from a Twitter page of a Manus AI report. And 90 pages report on a subject. I heard it is twice as long as OpenAI deep research on the same topic. And was just better
Optimizing Your E-Ecommerce Experience with ChatGPT
The guide titled "Shopping with ChatGPT" leverages reasoning, search, deep research, and operator assistance to enhance the shopping experience. It is divided into two main categories: Recommendations and Promo Codes, each with Quick and Deep approaches.
For Recommendations, the Quick method uses models like o1 and o3-mini-high with prompts such as suggesting brands based on user preferences or finding a brand for a specific product. The Deep method employs the Deep Research model to research product characteristics and identify the best option.
For Promo Codes, the Quick approach uses the o3-mini-high + Search model to find codes for a specific brand, while the Deep approach uses the Operator model to find and validate promo codes for a desired product. This structured approach aims to streamline and optimize the shopping process using advanced AI capabilities.
@webthreeth
The guide titled "Shopping with ChatGPT" leverages reasoning, search, deep research, and operator assistance to enhance the shopping experience. It is divided into two main categories: Recommendations and Promo Codes, each with Quick and Deep approaches.
For Recommendations, the Quick method uses models like o1 and o3-mini-high with prompts such as suggesting brands based on user preferences or finding a brand for a specific product. The Deep method employs the Deep Research model to research product characteristics and identify the best option.
For Promo Codes, the Quick approach uses the o3-mini-high + Search model to find codes for a specific brand, while the Deep approach uses the Operator model to find and validate promo codes for a desired product. This structured approach aims to streamline and optimize the shopping process using advanced AI capabilities.
@webthreeth
Gemini's Next Leap: Unveiling Gemini 2.0 Flash Thinking and Personalisation Experimental
Google is expected to unveil two new Gemini models: Gemini 2.0 Flash Thinking and Gemini 2.0 Personalisation Experimental
Gemini 2.0 Flash Thinking, evolving from its experimental roots, is anticipated to be a stable, production-ready version that blends the speed of the Flash architecture with enhanced reasoning capabilities, designed to break down complex prompts into transparent, step-by-step solutions—ideal for tasks requiring multi-step logic or multimodal inputs like text and images.
Meanwhile, Gemini 2.0 Personalisation Experimental is rumored to introduce a groundbreaking focus on user-tailored AI, potentially leveraging integration with Google services like Search, Maps, and YouTube to adapt responses to individual preferences or contexts, pushing the boundaries of agentic AI for more interactive and personalized experiences.
@webthreeth
Google is expected to unveil two new Gemini models: Gemini 2.0 Flash Thinking and Gemini 2.0 Personalisation Experimental
Gemini 2.0 Flash Thinking, evolving from its experimental roots, is anticipated to be a stable, production-ready version that blends the speed of the Flash architecture with enhanced reasoning capabilities, designed to break down complex prompts into transparent, step-by-step solutions—ideal for tasks requiring multi-step logic or multimodal inputs like text and images.
Meanwhile, Gemini 2.0 Personalisation Experimental is rumored to introduce a groundbreaking focus on user-tailored AI, potentially leveraging integration with Google services like Search, Maps, and YouTube to adapt responses to individual preferences or contexts, pushing the boundaries of agentic AI for more interactive and personalized experiences.
@webthreeth
Speculation of new model realesed of DeepSeek R2 on March 17
With whispers of a March 17 debut—accelerated from an original early May timeline—DeepSeek R2 promises to build on the success of its predecessor, R1, with enhanced capabilities that could redefine cost-effective AI innovation.
Analysts speculate R2 could also expand its multimodal capabilities, building on R1’s foundation to handle text, code, and possibly even images or other data types.
This versatility, paired with pricing rumored to be 20 to 40 times cheaper than OpenAI’s offerings, positions DeepSeek to capture a massive share of the developer and enterprise markets.
The R1 launch triggered a $1 trillion sell-off in global equities, as investors questioned the value of hardware-heavy AI strategies. R2’s arrival could amplify this disruption, especially if it delivers on its promise of enhanced coding and multilingual reasoning.
@webthreeth
With whispers of a March 17 debut—accelerated from an original early May timeline—DeepSeek R2 promises to build on the success of its predecessor, R1, with enhanced capabilities that could redefine cost-effective AI innovation.
Analysts speculate R2 could also expand its multimodal capabilities, building on R1’s foundation to handle text, code, and possibly even images or other data types.
This versatility, paired with pricing rumored to be 20 to 40 times cheaper than OpenAI’s offerings, positions DeepSeek to capture a massive share of the developer and enterprise markets.
The R1 launch triggered a $1 trillion sell-off in global equities, as investors questioned the value of hardware-heavy AI strategies. R2’s arrival could amplify this disruption, especially if it delivers on its promise of enhanced coding and multilingual reasoning.
@webthreeth
The Breakneck Evolution of AI: How Reasoning Models Are Shattering Historical Performance Trends
AI's recent breakthroughs in mathematical reasoning mark a sharp deviation from historical performance trends, with reasoning models vastly outperforming traditional frontier models in a short time. This suggests that AI is moving beyond brute-force computation toward more advanced reasoning, driven by improvements in architecture and training.
As AI continues to exceed expectations, tasks once thought resistant to automation—such as complex problem-solving and scientific research—may soon be within its reach, potentially disrupting expertise-driven industries. Given this rapid acceleration, linear extrapolations of AI progress are likely outdated, and we should anticipate sudden breakthroughs and emergent capabilities that redefine AI’s potential.
@webthreeth
AI's recent breakthroughs in mathematical reasoning mark a sharp deviation from historical performance trends, with reasoning models vastly outperforming traditional frontier models in a short time. This suggests that AI is moving beyond brute-force computation toward more advanced reasoning, driven by improvements in architecture and training.
As AI continues to exceed expectations, tasks once thought resistant to automation—such as complex problem-solving and scientific research—may soon be within its reach, potentially disrupting expertise-driven industries. Given this rapid acceleration, linear extrapolations of AI progress are likely outdated, and we should anticipate sudden breakthroughs and emergent capabilities that redefine AI’s potential.
@webthreeth
Meta’s AI Future: Partnering with TSMC for Custom Chip Innovation
Meta is making significant strides in reducing its reliance on external chip providers by developing its own AI training chip in collaboration with Taiwan Semiconductor Manufacturing Company (TSMC).
Currently in the testing phase as of March 11, 2025, this custom-designed chip aims to serve as a dedicated accelerator for AI tasks, offering greater efficiency compared to traditional GPUs. If successful, Meta plans to expand its deployment, partnering with TSMC, the world’s leading contract chip manufacturer, to produce this innovative hardware.
This move not only highlights Meta’s ambition to optimize its AI infrastructure and cut costs but also underscores TSMC’s pivotal role in powering the next generation of AI technologies for major tech firms.
@webthreeth
Meta is making significant strides in reducing its reliance on external chip providers by developing its own AI training chip in collaboration with Taiwan Semiconductor Manufacturing Company (TSMC).
Currently in the testing phase as of March 11, 2025, this custom-designed chip aims to serve as a dedicated accelerator for AI tasks, offering greater efficiency compared to traditional GPUs. If successful, Meta plans to expand its deployment, partnering with TSMC, the world’s leading contract chip manufacturer, to produce this innovative hardware.
This move not only highlights Meta’s ambition to optimize its AI infrastructure and cut costs but also underscores TSMC’s pivotal role in powering the next generation of AI technologies for major tech firms.
@webthreeth
Crypto Market Volatility in March 2025: A Shift in Sentiment
As of March 2025, the crypto market, particularly Bitcoin, is experiencing significant volatility, with the price dropping 5.3% to $78,354.89. This decline reflects a broader shift in market sentiment from extreme greed to fear, driven by a sudden change in risk appetite, as institutional capital exited tech stocks and built the largest Ethereum short position in history on February 9, 2025.
The announcement of a U.S. Strategic Crypto Reserve in early March initially sent crypto prices soaring, but it quickly turned into a "sell the news" event, exacerbating the downturn and aligning with the thread's analysis of deep red market days and massive outflows, such as the record $2.6 billion crypto fund outflow in late February 2025.
@webthreeth
As of March 2025, the crypto market, particularly Bitcoin, is experiencing significant volatility, with the price dropping 5.3% to $78,354.89. This decline reflects a broader shift in market sentiment from extreme greed to fear, driven by a sudden change in risk appetite, as institutional capital exited tech stocks and built the largest Ethereum short position in history on February 9, 2025.
The announcement of a U.S. Strategic Crypto Reserve in early March initially sent crypto prices soaring, but it quickly turned into a "sell the news" event, exacerbating the downturn and aligning with the thread's analysis of deep red market days and massive outflows, such as the record $2.6 billion crypto fund outflow in late February 2025.
@webthreeth
Tencent's Hunyuan-TurboS: Revolutionizing AI with Hybrid Efficiency and Superior Performance
Hunyuan-TurboS, developed by Tencent, is an innovative ultra-large Hybrid-Transformer-Mamba MoE model that combines Mamba's efficient long-sequence processing with Transformer's strong contextual understanding to overcome the O(N²) complexity and KV-Cache issues of traditional Transformer models.
This hybrid architecture enables Hunyuan-TurboS to outperform competitors like GPT-4o-0806 and DeepSeek-V3 in math, reasoning, and alignment benchmarks, while offering 1/7 lower inference costs than its predecessor, thanks to advancements such as slow-thinking integration, refined instruction tuning, and an upgraded reward system that enhances accuracy in STEM, QA, and creativity. Building on Tencent's earlier integration of AI models like Deepseek-R1 Ki into WeChat/Weixin in February 2025, Hunyuan-TurboS marks a significant step in the global AI race toward more intuitive and efficient AI solutions.
@webthreeth
Hunyuan-TurboS, developed by Tencent, is an innovative ultra-large Hybrid-Transformer-Mamba MoE model that combines Mamba's efficient long-sequence processing with Transformer's strong contextual understanding to overcome the O(N²) complexity and KV-Cache issues of traditional Transformer models.
This hybrid architecture enables Hunyuan-TurboS to outperform competitors like GPT-4o-0806 and DeepSeek-V3 in math, reasoning, and alignment benchmarks, while offering 1/7 lower inference costs than its predecessor, thanks to advancements such as slow-thinking integration, refined instruction tuning, and an upgraded reward system that enhances accuracy in STEM, QA, and creativity. Building on Tencent's earlier integration of AI models like Deepseek-R1 Ki into WeChat/Weixin in February 2025, Hunyuan-TurboS marks a significant step in the global AI race toward more intuitive and efficient AI solutions.
@webthreeth
AI's Uneven Impact on Global Employment
The chart illustrates the varying impact of AI on jobs across different economic regions, highlighting a stark contrast in exposure and complementarity. In advanced economies, a significant share of employment—around 60%—is highly exposed to AI, with roughly half of that share showing high complementarity, meaning AI can enhance these roles rather than replace them.
Globally, about 40% of jobs are highly exposed to AI, but this figure drops in emerging markets and low-income countries, where exposure is closer to 30% and 20%, respectively. In these regions, the share of jobs with high complementarity is also lower, indicating that AI is more likely to automate tasks without adding value to human roles.
This data underscores how AI's influence is predominantly felt in wealthier nations, potentially widening the technological and economic gap with emerging and low-income countries.
@webthreeth
The chart illustrates the varying impact of AI on jobs across different economic regions, highlighting a stark contrast in exposure and complementarity. In advanced economies, a significant share of employment—around 60%—is highly exposed to AI, with roughly half of that share showing high complementarity, meaning AI can enhance these roles rather than replace them.
Globally, about 40% of jobs are highly exposed to AI, but this figure drops in emerging markets and low-income countries, where exposure is closer to 30% and 20%, respectively. In these regions, the share of jobs with high complementarity is also lower, indicating that AI is more likely to automate tasks without adding value to human roles.
This data underscores how AI's influence is predominantly felt in wealthier nations, potentially widening the technological and economic gap with emerging and low-income countries.
@webthreeth
Gemma 3 27B IT: Pioneering High Performance with Minimal Size
Google unveiled Gemma 3, the latest lightweight, open-source AI model, designed for devices from smartphones to workstations. Available in four sizes—1B, 4B, 12B, and 27B parameters—it enables efficient, high-performing apps on a single GPU or TPU.
Gemma 3 27B IT stands out with an ELO score of 1,340, surpassing Meta Llama 3.1 405B (1,280 ELO) despite its 405 billion parameters, highlighting efficiency over scale. Compared to DeepSeek R1 (1,380 ELO, likely larger) and DeepSeek V3 (1,320 ELO), Gemma 3 excels with 27 billion parameters, outpacing Mistral Large 2407 (1,250 ELO, 200B) and Llama 3.3 70B (1,260 ELO, 70B). Models like Qwen 2.5 72B and Meta Llama 3.1 70B also lag at 1,260 ELO, underscoring Gemma 3’s optimization.
@webthreeth
Google unveiled Gemma 3, the latest lightweight, open-source AI model, designed for devices from smartphones to workstations. Available in four sizes—1B, 4B, 12B, and 27B parameters—it enables efficient, high-performing apps on a single GPU or TPU.
Gemma 3 27B IT stands out with an ELO score of 1,340, surpassing Meta Llama 3.1 405B (1,280 ELO) despite its 405 billion parameters, highlighting efficiency over scale. Compared to DeepSeek R1 (1,380 ELO, likely larger) and DeepSeek V3 (1,320 ELO), Gemma 3 excels with 27 billion parameters, outpacing Mistral Large 2407 (1,250 ELO, 200B) and Llama 3.3 70B (1,260 ELO, 70B). Models like Qwen 2.5 72B and Meta Llama 3.1 70B also lag at 1,260 ELO, underscoring Gemma 3’s optimization.
@webthreeth
Web 3.0 Ethiopia - DeFi & AI
Gemma 3 27B IT: Pioneering High Performance with Minimal Size Google unveiled Gemma 3, the latest lightweight, open-source AI model, designed for devices from smartphones to workstations. Available in four sizes—1B, 4B, 12B, and 27B parameters—it enables…
This is very huge for AI development. Parameters refer to variables that a model learns during its training to make predictions. Gemma has achieved a similar level of performance to DeepSeek R1 (which is currently the best open-source model) while training with 30X fewer parameters. This further pushes the frontier of AI development in the future.
@webthreeth
@webthreeth
The Disconnect Between Benchmark Scores and User Preferences
The graph highlights a significant disparity between traditional benchmark metrics and actual user preferences in AI model performance. It compares GPT-4.5 and DeepSeek V3, showing a modest 3.5% difference in Elo scores (1411 for GPT-4.5 vs. 1363 for DeepSeek V3), suggesting a close competition. However, user preference data reveals a stark contrast, with 74% of users favoring GPT-4.5 over DeepSeek V3's 26%.
This indicates that small differences in headline benchmarks can translate into a strong majority preference among users, a pattern observed across other similar model pairings. Sourced from LMArena, the data underscores the limitations of relying solely on Elo scores and emphasizes the importance of user experience in evaluating AI model effectiveness.
@webthreeth
The graph highlights a significant disparity between traditional benchmark metrics and actual user preferences in AI model performance. It compares GPT-4.5 and DeepSeek V3, showing a modest 3.5% difference in Elo scores (1411 for GPT-4.5 vs. 1363 for DeepSeek V3), suggesting a close competition. However, user preference data reveals a stark contrast, with 74% of users favoring GPT-4.5 over DeepSeek V3's 26%.
This indicates that small differences in headline benchmarks can translate into a strong majority preference among users, a pattern observed across other similar model pairings. Sourced from LMArena, the data underscores the limitations of relying solely on Elo scores and emphasizes the importance of user experience in evaluating AI model effectiveness.
@webthreeth
AI-Powered Farming Revolution in Ethiopia
The recent Memorandum of Understanding (MOU) between Ethiopia's Industrial Parks Development Corporation (IPDC) and Africa Farming Industries (AFI) marks a significant leap forward in agricultural innovation, with the introduction of an AI-powered vertical farming system. This cutting-edge technology, part of a two-million-dollar investment in the Bole Lemi Special Economic Zone, is set to enable year-round production of premium strawberries and saffron.
By leveraging artificial intelligence, the system ensures high yields and strict quality control, addressing seasonal limitations and boosting efficiency. This initiative not only modernizes Ethiopia's agricultural sector but also positions the country as a global player in exporting high-value crops, aligning with its broader goals of increasing foreign direct investment and sustainable development.
@webthreeth
The recent Memorandum of Understanding (MOU) between Ethiopia's Industrial Parks Development Corporation (IPDC) and Africa Farming Industries (AFI) marks a significant leap forward in agricultural innovation, with the introduction of an AI-powered vertical farming system. This cutting-edge technology, part of a two-million-dollar investment in the Bole Lemi Special Economic Zone, is set to enable year-round production of premium strawberries and saffron.
By leveraging artificial intelligence, the system ensures high yields and strict quality control, addressing seasonal limitations and boosting efficiency. This initiative not only modernizes Ethiopia's agricultural sector but also positions the country as a global player in exporting high-value crops, aligning with its broader goals of increasing foreign direct investment and sustainable development.
@webthreeth
Hedra's Character-3: Revolutionizing Video Creation with Omnimodal AI
The Character-3 model, launched by Hedra as part of its video generation platform, represents a significant leap in AI-driven content creation, introduced alongside Hedra Studio around March 6, 2025, based on current posts on X and web mentions. Billed as the first omnimodal AI model in production, Character-3 uniquely integrates image, text, and audio inputs to generate highly expressive, animated characters with natural movements, precise lip-syncing, and full-body motion capture.
This model allows users to upload a single image and pair it with audio or text prompts to produce dynamic, realistic videos—up to 90 seconds long—featuring talking, singing, or even rapping characters, all within minutes. Aimed at creators, marketers, and educators, Character-3 offers advanced customization options like emotional control and dynamic backgrounds, setting it apart from earlier models like Character-1 by delivering unparalleled realism and a seamless, unified workflow for storytelling.
@webthreeth
The Character-3 model, launched by Hedra as part of its video generation platform, represents a significant leap in AI-driven content creation, introduced alongside Hedra Studio around March 6, 2025, based on current posts on X and web mentions. Billed as the first omnimodal AI model in production, Character-3 uniquely integrates image, text, and audio inputs to generate highly expressive, animated characters with natural movements, precise lip-syncing, and full-body motion capture.
This model allows users to upload a single image and pair it with audio or text prompts to produce dynamic, realistic videos—up to 90 seconds long—featuring talking, singing, or even rapping characters, all within minutes. Aimed at creators, marketers, and educators, Character-3 offers advanced customization options like emotional control and dynamic backgrounds, setting it apart from earlier models like Character-1 by delivering unparalleled realism and a seamless, unified workflow for storytelling.
@webthreeth
PS - I made it Indian Accent just for the fun of it, but here is how the video goes, I think it is very good quality.
Imagen 3: Redefining Photorealism in AI Image Generation
Imagen 3, Google’s latest text-to-image model integrated into the Gemini ecosystem, represents a significant leap in AI-driven image generation as of March 2025. Launched globally to Gemini users around October 2024, Imagen 3 is celebrated for its exceptional photorealism, delivering sharper details, richer textures, and fewer visual artifacts than its predecessors.
It excels at interpreting natural language prompts with remarkable precision, enabling it to create diverse outputs ranging from lifelike scenes to stylized artworks like oil paintings or 3D digital renders. Built with improved safety filters and trained on enhanced datasets, Imagen 3 reflects Google’s focus on quality and responsibility, making it a versatile tool for creators. Its seamless integration with Gemini’s multimodal capabilities allows users to generate high-quality visuals directly within a conversational AI experience.
@webthreeth
Imagen 3, Google’s latest text-to-image model integrated into the Gemini ecosystem, represents a significant leap in AI-driven image generation as of March 2025. Launched globally to Gemini users around October 2024, Imagen 3 is celebrated for its exceptional photorealism, delivering sharper details, richer textures, and fewer visual artifacts than its predecessors.
It excels at interpreting natural language prompts with remarkable precision, enabling it to create diverse outputs ranging from lifelike scenes to stylized artworks like oil paintings or 3D digital renders. Built with improved safety filters and trained on enhanced datasets, Imagen 3 reflects Google’s focus on quality and responsibility, making it a versatile tool for creators. Its seamless integration with Gemini’s multimodal capabilities allows users to generate high-quality visuals directly within a conversational AI experience.
@webthreeth
Web 3.0 Ethiopia - DeFi & AI
Imagen 3: Redefining Photorealism in AI Image Generation Imagen 3, Google’s latest text-to-image model integrated into the Gemini ecosystem, represents a significant leap in AI-driven image generation as of March 2025. Launched globally to Gemini users around…
Here is an example of an Gameplay that was done by Imagen 3 from scratch with a matter of minutes. Is this impressive? Please click 👍. If you find it as one
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