Shopify’s 100+ Updates: AI a Key Theme
Plus: OpenAI explores how good GPT-4 is at creating bioweapons, LLaVA-1.6 releases.
Hello Engineering Leaders and AI Enthusiasts!
Welcome to the 201st edition of The AI Edge newsletter. This edition brings you Shopify’s newest AI enhancements.
And a huge shoutout to our amazing readers. We appreciate you😊
In today’s edition:
🛍️Shopify boosts its commerce platform with AI enhancements
🚫 OpenAI explores how good GPT-4 is at creating bioweapons
🚀 LLaVA-1.6: Improved reasoning, OCR, and world knowledge
📚 Knowledge Nugget: Quick Essay: Large Language Models, How to Train Them, and xAI’s Grok by
Let’s go!
Shopify boosts its commerce platform with AI enhancements
Shopify unveiled over 100 new updates to its commerce platform, with AI emerging as a key theme. The new AI-powered capabilities are aimed at helping merchants work smarter, sell more, and create better customer experiences.
The headline feature is Shopify Magic, which applies different AI models to assist merchants in various ways. This includes automatically generating product descriptions, FAQ pages, and other marketing copy. Early tests showed Magic can create SEO-optimized text in seconds versus the minutes typically required to write high-converting product blurbs.
On the marketing front, Shopify is infusing its Audiences ad targeting tool with more AI to optimize campaign performance. Its new semantic search capability better understands search intent using natural language processing.
Why does this matter?
The AI advancements could provide Shopify an edge over rivals. In addition, the new features will help merchants capitalize on the ongoing boom in online commerce and attract more customers across different channels and markets. This also reflects broader trends in retail and e-commerce, where AI is transforming everything from supply chains to customer service.
OpenAI explores how good GPT-4 is at creating bioweapons
OpenAI is developing a blueprint for evaluating the risk that a large language model (LLM) could aid someone in creating a biological threat.
In an evaluation involving both biology experts and students, it found that GPT-4 provides at most a mild uplift in biological threat creation accuracy. While this uplift is not large enough to be conclusive, the finding is a starting point for continued research and community deliberation.
Why does this matter?
LLMs could accelerate the development of bioweapons or make them accessible to more people. OpenAI is working on an early warning system that could serve as a "tripwire" for potential misuse and development of biological weapons.
LLaVA-1.6: Improved reasoning, OCR, and world knowledge
LLaVA-1.6 releases with improved reasoning, OCR, and world knowledge. It even exceeds Gemini Pro on several benchmarks. Compared with LLaVA-1.5, LLaVA-1.6 has several improvements:
Increasing the input image resolution to 4x more pixels.
Better visual reasoning and OCR capability with an improved visual instruction tuning data mixture.
Better visual conversation for more scenarios, covering different applications.Better world knowledge and logical reasoning.
Efficient deployment and inference with SGLang.
Along with performance improvements, LLaVA-1.6 maintains the minimalist design and data efficiency of LLaVA-1.5. The largest 34B variant finishes training in ~1 day with 32 A100s.
Why does this matter?
LLaVA-1.6 is an upgrade to LLaVA-1.5, which has a simple and efficient design and great performance akin to GPT-4V.. LLaVA-1.5 has since served as the foundation of many comprehensive studies of data, models, and capabilities of large multimodal models (LMM) and has enabled various new applications. It shows the growing open-source AI community with fast-moving and freewheeling standards.
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Knowledge Nugget: Quick Essay: Large Language Models, How to Train Them, and xAI’s Grok
When OpenAI released ChatGPT in November 2022, it took the world by storm. Since then, there has been an explosion in AI activity, ranging from applications built on top of ChatGPT which seek to improve efficiency for mundane tasks to new chatbots like xAI’s Grok which aim to replace ChatGPT altogether.
This explosion happened so quickly that few of us really took a step back to understand the basics. So, in this article,
helps us understand how LLMs work to determine how new entrants like xAI will compete. The article also discusses how do you build an LLM and highlights xAI's unique approach.Why does this matter?
As the foundational layer of language models is becoming increasingly difficult to improve with more data, the quality of the data that these models are trained on becomes a key differentiator. With high-quality real-time data and the capital to scale, Grok has the opportunity to become the most up-to-date, customizable and context-aware language model in the race to achieve AGI.
What Else Is Happening❗
🎯Microsoft LASERs away LLM inaccuracies.
Microsoft Research introduces Layer-Selective Rank Reduction (or LASER). While the method seems counterintuitive, it makes models trained on large amounts of data smaller and more accurate. With LASER, researchers can “intervene” and replace one weight matrix with an approximate smaller one. (Link)
🚀Mistral CEO confirms ‘leak’ of new open source model nearing GPT-4 performance.
A user with the handle “Miqu Dev” posted a set of files on HuggingFace that together comprised a seemingly new open-source LLM labeled “miqu-1-70b.” Mistral co-founder and CEO Arthur Mensch took to X to clarify and confirm. Some X users also shared what appeared to be its exceptionally high performance at common LLM tasks, approaching OpenAI’s GPT-4 on the EQ-Bench. (Link)
🎬Synthesia launches LLM-powered assistant to turn any text file or link into AI video.
Synthesia launched a tool to turn text-based sources into full-fledged synthetic videos in minutes. It builds on Synthesia’s existing offerings and can work with any document or web link, making it easier for enterprise teams to create videos for internal and external use cases. (Link)
👗AI is helping pick what you'll wear in two years.
Fashion forecasters are leveraging AI to make decisions about the trends and styles you’ll be scrambling to wear. A McKinsey survey found that 73% of fashion executives said GenAI will be a business priority next year. AI predicts trends by scraping social media, evaluating runway looks, analyzing search data, and generating images. (Link)
💻Twin Labs automates repetitive tasks by letting AI take over your mouse cursor.
Paris-based startup Twin Labs wants to build an automation product for repetitive tasks, but what’s interesting is how they’re doing it. The company relies on models like GPT-4V) to replicate what humans usually do. Twin Labs is more like a web browser. The tool can automatically load web pages, click on buttons, and enter text. (Link)
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