Sugar.fit initially raised $10 million in a seed funding round and has reportedly wtinessed exceptional growth. In the last 18 months, the brand has witnessed eightfold growth in paid subscribers, and currently serves more than 25,

Sugar.fit secures $11 million in Series A funding; To focus on expansion and R&D for diabetes management

and somehow increase their number of streams eightfold. (There goes Consequence‘s next big business venture. [Kidding!]) It’s worth noting that news arrives just a month after Universal/Deezer announced their own “artist-centric” model, which ...

Spotify’s New Royalty Model Will Focus on “Legitimate” Artists Who Meet Certain Thresholds

Husk Power secured over US$100 million in equity and debt funding aimed to grow its mini-grids in sub-Saharan Africa and South Asia.

Husk Power secures US$100 million to grow community solar mini-grids in sub-Saharan Africa and South Asia

Players will be able to earn some special rewards in Tears of the Kingdom by scanning certain Amiibos, with these being among the best.

Tears Of The Kingdom: 7 Most Rewarding Amiibos, Ranked

Running on AWS, Wallbox has been able to expand its year-over-year US sales in the second quarter of 2023 by 67 percent with the help of its new Texas-based factory, opened in 2022. This site alone can currently produce 250,000 chargers a year and will produce 1 million chargers annually by 2030.

Solving Drivers’ EV Charging Woes

So, although net fee income (NFI) dipped from £44.2mn to £43.4mn, profitability surged, so much so that underlying pre-tax profit rose eightfold to £2.6mn as the conversion rate of NFI to operating profit rocketed.

Profits are surging at this high yield recovery play

The 87-degree high on Friday was the 143rd day this year with a high of at least 80 degrees, which broke the previous record of 142 set last year.

October heat helps Lincoln break record for 80-degree days

While it has been warmer in Earth’s distant past, it is increasingly likely that 2023 will be the hottest calendar year since human civilizations began to develop — once the last ice age ended around 10,000 years ago. Figuring out the global climate ...

How we know past climate without thermometers

We want to hear from you! Have a question for the meteorologists? Call 609-272-7099 and leave a message. You might hear your question and get an answer on a future episode! You can also email questions or comments to podcasts@lee.net. About the Across the ...

Eightfold

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The Eightfold Path of the Legendary Trader

Unlocking the Secrets of Autocatalytic Sets: How Bit Strings and Reactions Shape Molecular Evolution

We live in the era of large language models (LLMs), with companies increasingly deploying models with billions of parameters. These expansive models unlock new possibilities for users but come with high deployment costs and complexity, especially on personal computers. As a result, researchers and engineers often train these large models first and then compress them while trying to minimize quality loss. Models are released in the float16 format, where 16 bits are allocated for each weight. Two years ago, technological advancement got us to the point where we can reliably compress neural networks down to 4 bits using techniques like GPTQ. But progress doesn't stop here, as the research community is now actively seeking methods to reduce model size eightfold, down to 2 bits. A little while ago, the Yandex Research team joined efforts with their colleagues from IST Austria and KAUST to introduce a new method of achieving 8x compression through the combined use of AQLM and PV-Tuning. This method has been made publicly available to software developers and researchers, with the code published in a GitHub repository. Examples of popular open-source models that were compressed using this method can be downloaded here. For fine-tuning a compressed neural network, take a look at these training materials to fine-tune a compressed neural network. We want to shed some light on how the method was developed thanks to a brief (albeit very exciting!) "rivalry" between two research teams and their state-of-the-art compression algorithms: QuIP and AQLM. Competition fuels innovation, and this rapidly evolving story is a prime example. Every other month brings breakthroughs, optimizations, and ingenious solutions. Sit back and enjoy! Methodology In our example, we'll be using Llama2 13b. Along with it, Meta released two more models, 7b and 70b. In academic research, perplexity is typically used to assess the quality of compressed models. This metric measures how perplexed (hence the name) a neural network gets after seeing correctly written text. Lower perplexity means a better model. We've chosen a different primary metric for this article: effective model size. When plotting perplexity against model size, all three Llama2 models fall on the same line so that we can report a more intuitive metric. Quantization of LLMs With Guarantees In mid-2023, a group of scientists from Cornell University published an article titled QuIP, where the authors seriously discussed for the first time the possibility of compressing neural networks by a factor of 8 for the first time. The idea is that 99% of weights in large language models behave similarly and can be easily compressed with minimal loss. However, the remaining 1% — outliers — significantly deviate from the norm and lead to inaccuracies during compression. The QuIP authors devised a technique to shuffle these weights, effectively solving the outlier problem. The algorithm compresses Llama2 13b to a perplexity of 13.5. At first glance, this may seem like a poor result, as it corresponds to a model with a mere size of 0.43M parameters. But this was the first time the perplexity remained in the double digits after compression. For reference, GPTQ compresses the same model to a perplexity of 123. So, what QuIP managed to achieve was nothing short of a breakthrough. Extreme Compression of LLMs via Additive Quantization Six months later, in January 2024, researchers from Yandex and the Institute of Science and Technology Austria (ISTA) published a paper on additive quantization for language models (AQLM). The method relies on additive quantization proposed in 2014 by Artem Babenko, Head of Yandex Research — back then, it was intended to help the company's search engine needs. Ten years later, this technology was repurposed to compress large language models while maintaining maximum quality. AQLM compresses Llama 13b to a perplexity that corresponds to the 3.7b model. This was a significant improvement over QuIP — a model like that was now actually usable. A Close Competition — Upgrade From QuiP to QuIP# Just a month later, researchers from Cornell struck back with a new study titled "QuIP#." The authors refined their method with fine-tuning and other optimizations, showing that you can fine-tune a compressed neural network on a calibrated dataset to significantly reduce compression error without changing the model's representation format. QuIP# performed better than AQLM, improving the SOTA quantization of the Llama2-13b model to an effective size of 5.3B parameters. A New Chapter for AQLM In late May, a joint study by the creators of AQLM and researchers from King Abdullah University of Science and Technology (KAUST) saw light. The authors propose an advanced fine-tuning algorithm —  PV-Tuning — to improve on the old AQLM. While the QuIP# paper suggests fine-tuning only continuous parameters with gradients, PV-Tuning modifies all model parameters, including discrete ones. In terms of quality, this is the best algorithm for 2-bit quantization to date. It compresses the Llama 13b model to an effective size of 6.9B, falling just a bit short of the 7b model. Every year, neural network quantization becomes more and more efficient: inference costs are going down exponentially, and large models with open weights can now be launched on regular hardware. A few years ago, one could only dream of launching a large model like Llama3 70b on an RTX 3090. In 2024, that's already a reality. Healthy competition among researchers is a catalyst for technological advancement, driving innovation and the development of creative approaches. How will the story unfold from here? Time will tell! And we have a feeling it won't be long. We live in the era of large language models (LLMs), with companies increasingly deploying models with billions of parameters. These expansive models unlock new possibilities for users but come with high deployment costs and complexity, especially on personal computers. As a result, researchers and engineers often train these large models first and then compress them while trying to minimize quality loss. Models are released in the float16 format, where 16 bits are allocated for each weight. Two years ago, technological advancement got us to the point where we can reliably compress neural networks down to 4 bits using techniques like GPTQ . But progress doesn't stop here, as the research community is now actively seeking methods to reduce model size eightfold, down to 2 bits. GPTQ GPTQ A little while ago, the Yandex Research team joined efforts with their colleagues from IST Austria and KAUST to introduce a new method of achieving 8x compression through the combined use of AQLM and PV-Tuning. This method has been made publicly available to software developers and researchers, with the code published in a GitHub repository . GitHub repository GitHub repository Examples of popular open-source models that were compressed using this method can be downloaded here . For fine-tuning a compressed neural network, take a look at these training materials to fine-tune a compressed neural network. here here these training materials these training materials We want to shed some light on how the method was developed thanks to a brief (albeit very exciting!) "rivalry" between two research teams and their state-of-the-art compression algorithms: QuIP and AQLM. Competition fuels innovation, and this rapidly evolving story is a prime example. Every other month brings breakthroughs, optimizations, and ingenious solutions. Sit back and enjoy! Methodology Methodology In our example, we'll be using Llama2 13b. Along with it, Meta released two more models, 7b and 70b. In academic research, perplexity is typically used to assess the quality of compressed models. This metric measures how perplexed (hence the name) a neural network gets after seeing correctly written text. Lower perplexity means a better model. We've chosen a different primary metric for this article: effective model size. When plotting perplexity against model size, all three Llama2 models fall on the same line so that we can report a more intuitive metric. Quantization of LLMs With Guarantees Quantization of LLMs With Guarantees In mid-2023, a group of scientists from Cornell University published an article titled QuIP, where the authors seriously discussed for the first time the possibility of compressing neural networks by a factor of 8 for the first time. The idea is that 99% of weights in large language models behave similarly and can be easily compressed with minimal loss. However, the remaining 1% — outliers — significantly deviate from the norm and lead to inaccuracies during compression. The QuIP authors devised a technique to shuffle these weights, effectively solving the outlier problem. The algorithm compresses Llama2 13b to a perplexity of 13.5. At first glance, this may seem like a poor result, as it corresponds to a model with a mere size of 0.43M parameters. But this was the first time the perplexity remained in the double digits after compression. For reference, GPTQ compresses the same model to a perplexity of 123. So, what QuIP managed to achieve was nothing short of a breakthrough. Extreme Compression of LLMs via Additive Quantization Extreme Compression of LLMs via Additive Quantization Six months later, in January 2024, researchers from Yandex and the Institute of Science and Technology Austria (ISTA) published a paper on additive quantization for language models (AQLM). The method relies on additive quantization proposed in 2014 by Artem Babenko, Head of Yandex Research — back then, it was intended to help the company's search engine needs. paper paper Ten years later, this technology was repurposed to compress large language models while maintaining maximum quality. AQLM compresses Llama 13b to a perplexity that corresponds to the 3.7b model. This was a significant improvement over QuIP — a model like that was now actually usable. A Close Competition — Upgrade From QuiP to QuIP# A Close Competition — Upgrade From QuiP to QuIP# Just a month later, researchers from Cornell struck back with a new study titled "QuIP#." The authors refined their method with fine-tuning and other optimizations, showing that you can fine-tune a compressed neural network on a calibrated dataset to significantly reduce compression error without changing the model's representation format. new study new study QuIP# performed better than AQLM, improving the SOTA quantization of the Llama2-13b model to an effective size of 5.3B parameters. A New Chapter for AQLM A New Chapter for AQLM In late May, a joint study by the creators of AQLM and researchers from King Abdullah University of Science and Technology (KAUST) saw light. The authors propose an advanced fine-tuning algorithm —  PV-Tuning — to improve on the old AQLM. While the QuIP# paper suggests fine-tuning only continuous parameters with gradients, PV-Tuning modifies all model parameters, including discrete ones. propose propose In terms of quality, this is the best algorithm for 2-bit quantization to date. It compresses the Llama 13b model to an effective size of 6.9B, falling just a bit short of the 7b model. Every year, neural network quantization becomes more and more efficient: inference costs are going down exponentially, and large models with open weights can now be launched on regular hardware. A few years ago, one could only dream of launching a large model like Llama3 70b on an RTX 3090. In 2024, that's already a reality. Healthy competition among researchers is a catalyst for technological advancement, driving innovation and the development of creative approaches. How will the story unfold from here? Time will tell! And we have a feeling it won't be long.

The Extreme LLM Compression Evolution: From QuIP to AQLM With PV-Tuning

268 Stories To Learn About Trading

295 Stories To Learn About Cryptocurrency

153 Stories To Learn About Bitcoin

In the dynamic world of cryptocurrency, staying ahead means leveraging the expertise of specialized marketing agencies. These agencies offer invaluable services, from NFT promotion to influencer marketing, vital for projects seeking visibility and success in a crowded market. This guide explores the top 8 crypto marketing agencies of 2024, highlighting their unique offerings and why collaborating with them can be a game-changer for your crypto project. Coinband Coinband is the fastest-growing crypto marketing agency in 2024, having expanded eightfold within the year. Renowned for its prowess in user and investor acquisition within the crypto sphere, Coinband boasts over 1000 collaborations with KOLs and more than 400 media partnerships. Exclusive PPC advertising opportunities are offered through premium partnerships with Twitter, Google, and Meta. Among Coinband's esteemed clientele are industry giants such as ByBit, OKX, ChainGPT, DAO Maker, Poolz, Uniswap, and NEAR. With a dedicated team of over 40 professionals, Coinband is at the forefront of Web3 marketing, specializing in token sales for projects and post-listing stage development. As a leading web3 marketing agency for presale stage projects, Coinband consistently attracts daily investments ranging from $600,000 to $700,000 for its clients' projects, solidifying its position as a key player in the digital marketing landscape. CryptoVirally - The Premier Choice CryptoVirally stands out as the leading crypto marketing agency in 2024. With a comprehensive range of over 150 detailed packages, they offer transparent pricing directly on their website. Their limited-time offers, feature discounts of up to 70%, making their top-tier services accessible to a wider audience. Whether press releases, social media marketing, or full brand development, CryptoVirally tailors its services to maximize your project's reach and impact. Their approach ensures that your project not only gains organic visibility but also establishes a lasting presence in the crypto world. Explore CryptoVirally's Services EmergenceMedia.Agency EmergenceMedia.Agency specializes in creating compelling narratives for crypto projects. Their expertise in storytelling, combined with a deep understanding of the crypto market, enables them to craft campaigns that resonate with target audiences. They excel in media reach and influencer marketing, connecting projects with key voices in the industry to amplify their message. CryptoPR CryptoPR is renowned for its innovative approach to public relations in the crypto space. They focus on building strong media relationships, ensuring that your project gets coverage in top-tier crypto publications. Their team of PR experts works tirelessly to keep your project in the spotlight, driving awareness and engagement. Coinbound Coinbound is a trailblazer in digital marketing for the crypto industry. Their expertise in SEO and social media marketing helps projects gain organic traffic and a loyal following. Their strategies are data-driven, ensuring that every campaign delivers maximum ROI. TokenMinds TokenMinds stands out for its expertise in token marketing and community management. They understand the nuances of tokenomics and craft strategies that highlight the unique value proposition of your token. Their community management services ensure that your project maintains a positive and active presence in key crypto forums and social platforms. Blockchainmarketing.io Blockchainmarketing.io focuses on holistic marketing strategies for blockchain-based projects. Their services range from SEO optimization to targeted ad campaigns, ensuring that your project reaches its ideal audience. Their deep understanding of blockchain technology allows them to create campaigns that are not only creative but also technically sound. Omni Agency Omni Agency offers a comprehensive suite of marketing services tailored to the crypto industry. Their team excels in crafting personalized marketing plans that align with your project's goals. From content creation to analytics, they cover every aspect of marketing to ensure your project's success. NinjaPromo NinjaPromo is known for its creative and impactful social media campaigns. They leverage the latest trends and platforms to ensure your project stands out. Their team of social media experts understands the crypto audience, enabling them to create campaigns that engage and convert. Choose the Right Agency for Your Crypto Journey Selecting the right crypto marketing agency is crucial for your project's success. Each of these agencies brings unique strengths and expertise. Remember to check the detailed packages on CryptoVirally, offering transparency and affordability with their extensive service range. Their case studies and free consultations provide further insights into how they can elevate your project. In this ever-evolving crypto landscape, partnering with the right marketing agency can be your key to standing out and achieving lasting success. In the dynamic world of cryptocurrency, staying ahead means leveraging the expertise of specialized marketing agencies. These agencies offer invaluable services, from NFT promotion to influencer marketing, vital for projects seeking visibility and success in a crowded market. This guide explores the top 8 crypto marketing agencies of 2024, highlighting their unique offerings and why collaborating with them can be a game-changer for your crypto project. NFT Coinband Coinband is the fastest-growing crypto marketing agency in 2024, having expanded eightfold within the year. Renowned for its prowess in user and investor acquisition within the crypto sphere, Coinband boasts over 1000 collaborations with KOLs and more than 400 media partnerships. Exclusive PPC advertising opportunities are offered through premium partnerships with Twitter, Google, and Meta. Coinband Among Coinband's esteemed clientele are industry giants such as ByBit, OKX, ChainGPT, DAO Maker, Poolz, Uniswap, and NEAR. With a dedicated team of over 40 professionals, Coinband is at the forefront of Web3 marketing, specializing in token sales for projects and post-listing stage development. As a leading web3 marketing agency for presale stage projects, Coinband consistently attracts daily investments ranging from $600,000 to $700,000 for its clients' projects, solidifying its position as a key player in the digital marketing landscape. CryptoVirally - The Premier Choice CryptoVirally stands out as the leading crypto marketing agency in 2024. With a comprehensive range of over 150 detailed packages, they offer transparent pricing directly on their website. Their limited-time offers, feature discounts of up to 70%, making their top-tier services accessible to a wider audience. Whether press releases, social media marketing, or full brand development, CryptoVirally tailors its services to maximize your project's reach and impact. Their approach ensures that your project not only gains organic visibility but also establishes a lasting presence in the crypto world. Explore CryptoVirally's Services Explore CryptoVirally's Services EmergenceMedia.Agency EmergenceMedia.Agency specializes in creating compelling narratives for crypto projects. Their expertise in storytelling, combined with a deep understanding of the crypto market, enables them to craft campaigns that resonate with target audiences. They excel in media reach and influencer marketing, connecting projects with key voices in the industry to amplify their message. CryptoPR CryptoPR is renowned for its innovative approach to public relations in the crypto space. They focus on building strong media relationships, ensuring that your project gets coverage in top-tier crypto publications. Their team of PR experts works tirelessly to keep your project in the spotlight, driving awareness and engagement. Coinbound Coinbound is a trailblazer in digital marketing for the crypto industry. Their expertise in SEO and social media marketing helps projects gain organic traffic and a loyal following. Their strategies are data-driven, ensuring that every campaign delivers maximum ROI. TokenMinds TokenMinds stands out for its expertise in token marketing and community management. They understand the nuances of tokenomics and craft strategies that highlight the unique value proposition of your token. Their community management services ensure that your project maintains a positive and active presence in key crypto forums and social platforms. Blockchainmarketing.io Blockchainmarketing.io focuses on holistic marketing strategies for blockchain-based projects. Their services range from SEO optimization to targeted ad campaigns, ensuring that your project reaches its ideal audience. Their deep understanding of blockchain technology allows them to create campaigns that are not only creative but also technically sound. Omni Agency Omni Agency offers a comprehensive suite of marketing services tailored to the crypto industry. Their team excels in crafting personalized marketing plans that align with your project's goals. From content creation to analytics, they cover every aspect of marketing to ensure your project's success. NinjaPromo NinjaPromo is known for its creative and impactful social media campaigns. They leverage the latest trends and platforms to ensure your project stands out. Their team of social media experts understands the crypto audience, enabling them to create campaigns that engage and convert. Choose the Right Agency for Your Crypto Journey Selecting the right crypto marketing agency is crucial for your project's success. Each of these agencies brings unique strengths and expertise. Remember to check the detailed packages on CryptoVirally, offering transparency and affordability with their extensive service range. Their case studies and free consultations provide further insights into how they can elevate your project. In this ever-evolving crypto landscape, partnering with the right marketing agency can be your key to standing out and achieving lasting success.

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