Category: Top News

IBL News | New York

Generative AI is poised to unleash the next wave of productivity, stated McKinsey in a research titled “The economic potential of generative AI: The next productivity frontier,” released last month.

The ability of generative AI applications, built using foundation models, to write text, compose music, and create digital art has persuaded consumers and households to experiment on their own.

AI trained on these models can perform several functions; it can classify, edit, summarize, answer questions, and draft new content, among other tasks.

McKinsey’s research considers that we are at the beginning of a journey to understand generative AI’s power, reach, and capabilities.

“Deep learning has powered many of the recent advances in AI, but the foundation models powering generative AI applications are a step-change evolution within deep learning. Unlike previous deep learning models, they can process extremely large and varied sets of unstructured data and perform more than one task.”

Its research suggests that generative AI is poised to transform roles and boost performance across functions such as sales and marketing, customer operations, and software development.

In the process, it could unlock trillions of dollars in value across sectors from banking to life sciences.

Foundation models have enabled new capabilities and vastly improved existing ones across a broad range of modalities, including images, video, audio, and computer code. AI trained on these models can perform several functions; it can classify, edit, summarize, answer questions, and draft new content, among other tasks.
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IBL News | New York

Paris-based Mistral AI — which is trying to build an alternative to OpenAI’s GPT-4 and Anthropic’s Claude 2 — released yesterday a new LLM named Mistral Large. The model was not released under an open-source license.

In addition, the French start-up is launching its alternative to ChatGPT with a new service called Le Chat, now available in beta. Le Chat can’t access the web.

Founded by Mensch, Timothée Lacroix, and Guillaume Lample, a trio of former Meta and Google researchers, has now a valuation of €2 billion. [People working at Mistral in the picture above.]

It supports context windows of 32k tokens (generally more than 20,000 words in English) in English, French, Spanish, German, and Italian.

As a comparison, GPT-4 Turbo has a 128k-token context window.

Mistral AI made Mistral Large available through Microsoft’s Azure, its first distribution partner, after signing a “multi-year partnership.”

As part of the deal, Microsoft said it would invest in Mistral, although the financial details were not disclosed. The partnership will include a research and development collaboration to build applications for governments across Europe.

IBL News | San Diego

Since the Release of ChatGPT Upwork freelance website’s postings data — publicly available in the form of an RSS feed — show an increase in the number of jobs since ChatGPT was released in November 2022, according to the analysis of an expert posted at Bloomberry.com.

However, three categories showed a large decline in jobs: writing, translation, and customer service jobs. The number of writing jobs declined by 33%, translation jobs declined by 19%, and customer service jobs declined by 16%.

Since November 2022, video editing/production jobs were up 39%, graphic design jobs 8%, and web design jobs 10%. Software development jobs were also up, with backend development jobs at 6% and frontend/web development jobs at 4%.

“Generative AI tools are already good enough to replace many writing tasks, whether it’s writing an article or a social media post. But they’re not polished enough for other jobs like video and image generation,” said Henley Wing, the author of the analysis.

Jobs like generating AI content, developing AI agents, integrating OpenAI/ChatGPT APIs, and developing chatbots and AI apps are becoming the norm.

However, the vast majority of companies are not yet developing their own LLM models or tuning them with training data. They seem to be integrating OpenAI’s API into their existing products and developing chatbots to replace their customer service agents.

IBL News | New York

Google Meet announced last month an upcoming gesture detection feature called “Raise hand” for Q&A sessions and other moderation.

This is a button in the toolbar available for enterprise accounts on Google Workplace, which lets people know when you have something to say, as the webcam recognizes hands up.

The feature turns off gesture detection when someone is an active speaker.

Until now, raising your hand to ask a question in Google Meet was done by clicking the hand-raise icon.

This feature is toggled off by default and can be enabled from More Options > Reactions > Hand Raise Gesture.

It’s similar to how Google Camera in Pixel phones can start a selfie timer when you raise your palm.
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IBL News | San Diego

Adobe introduced this week an AI assistant in beta in Reader and Acrobat, which instantly generates summaries and insights from long PDF documents. It also recommends and answers questions based on a PDF’s content through an intuitive conversational interface.

The AI assistant generates citations with the source, and as an output, it formats the information for sharing in emails, reports, and presentations. Clickable links help quickly find information in long documents.

This feature will be sold through a new add-on subscription plan when AI Assistant is out of beta.

“Our AI Assistant is bringing generative AI to the masses, unlocking new value from the information inside the approximately 3 trillion PDFs in the world,” stated Adobe.

This assistant leverages the same AI and machine learning models behind Acrobat Liquid Mode, the technology that supports responsive reading experiences for PDFs on mobile.

PDF was invented by Adobe thirty years ago Adobe, and today remains the standard for reading, editing, and transforming PDFs.

Currently, the new AI Assistant features are available in beta for Acrobat Standard and Pro Individual and Teams subscription plans on desktop and web in English, with features coming to Reader desktop customers in English over the next few weeks – all at no additional cost. Other languages will follow. A private beta is available for enterprise customers.

• Adobe: How people are using AI Assistant (YouTube videos)

IBL News | San Diego

Google released yesterday Gemma 2B and 7B, two lightweight, pre-trained open-source AI models, mostly suitable for small developments such as simple chatbots or summarizations.

It also lets developers use the research and technology used to create the Gemini closed models.

They are available via Kaggle, Hugging Face, Nvidia’s NeMo, and Google’s Vertex AI. It’s designed with Google’s AI Principles at the forefront.

Gemma supports multi-framework Keras 3.0, native PyTorch, JAX, and Hugging Face Transformers.

Developers and researchers can work with Gemma using free access in Kaggle, a free tier for Colab notebooks, and $300 in credits for first-time Google Cloud users. Researchers can also apply for Google Cloud credits of up to $500,000 to accelerate their projects.

Each size of Gemma is available at ai.google.dev/gemma.

Google is also providing toolchains for inference and supervised fine-tuning (SFT) across all major frameworks: JAX, PyTorch, and TensorFlow through native Keras 3.0.

Google’s Gemini comes in several weights, including Gemini Nano, Gemini Pro, and Gemini Ultra.

Last week, Google announced a faster Gemini 1.5 intended for business users and developers.

Gemini 1.5 Pro's 1,000,000+ token context length is incredible.

I got early access and spent my Saturday night running tests.

Here are 6 impressive capabilities I found: pic.twitter.com/Rh8qGCUevE

— Rowan Cheung (@rowancheung) February 18, 2024

IBL News | New York

D2L Brightspace presented to selected customers new generative AI tools to generate practice and quiz questions as part of its LMS platform.

With this new program, which will be in testing mode through the summer of 2024, teachers are able to set quiz questions before making them available to students, giving them more safety and control oversight.

The beta program is based on D2L’s “Responsible AI Principles” document.

“This automated question generation capability can make it easier for instructors to assess learners in the moment. It is the initial step in expanding our product roadmap with cutting-edge generative AI to help change the way the world learns,” said Stephen Laster, D2L president.
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IBL News | New York

Khanmigo, Khan Academy’s ChatGPT-powered tutoring bot, makes frequent calculation errors, The Wall Street Journal reported after testing it. “We tested an AI tutor for kids. It struggled with basic math,” wrote the paper.

Last year, Educator Sal Khan promised to “give every student on the planet an artificially intelligent but amazing personal tutor.”

“Asking ChatGPT to do math is sort of like asking a goldfish to ride a bicycle—it’s just not what ChatGPT is for,” said Tom McCoy, a professor at Yale University who studies AI.

According to the paper, “Khanmigo frequently made basic arithmetic errors, miscalculating subtraction problems such as 343 minus 17. It also didn’t consistently know how to round answers or calculate square roots. Khanmigo typically didn’t correct mistakes when asked to double-check solutions.”

Now being piloted by about 65,000 students in 44 school districts, Khanmigo emphasizes to students and teachers that it is imperfect.

Sal Khan said he expects “a million or two million” students to be using it by next school year at a price to schools of $35 a student.

Unlike ChatGPT, Khanmigo is trained not to give students the right answer but to guide them through problems. It offers tutoring in third grade and up in math, language arts, history and science. It can give feedback on student essays, engage in simulated dialogue as famous literary characters and debate contemporary issues.

In testing the product, the WSJ asked Khanmigo for help finding the length of the third side of a right triangle, a problem that students would likely encounter in eighth-grade math.

Khanmigo correctly identified the Pythagorean theorem, a² + b² = c², as crucial to finding the answer. When asked for the solution the bot offered responses such as: “I’m here to help you learn, not just give answers!”

But Khanmigo struggled with math operations. When trying to solve a right triangle with a hypotenuse of 27 units and a side of 17, a reporter offered the wrong answer (430 rather than 440) to 27² minus 17². “Excellent!” Khanmigo responded. Later, it accepted the incorrect answer to the square root of 440.

In another instance, Khanmigo constructed its own triangle problem with a hypotenuse of 15 units and a leg of nine. But when a reporter correctly said that 15² minus 9² equals 144, Khanmigo suggested the response was wrong. “I see where you’re coming from, but let’s take another look at the subtraction,” it said.
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IBL News | New York

Amazon launched this month in beta an AI-powered shopping assistant called ‘Rufus’, trained on the company product catalog, customer reviews, community Q&As, and information from across the web. It’s available to select customers when they next update their Amazon Shopping app.

Built on an internal LLM specialized for shopping, this conversational assistant answers customer questions on a variety of shopping needs and products, provide comparisons, and make recommendations based on conversational context.

“Rufus knows Amazon’s selection inside and out, and can bring it all together with information from across the web to help them make more informed purchase decisions,” said Amazon.

“With Rufus, customers can:

• Learn what to look for while shopping product categories: Customers can conduct more general product research on Amazon, asking questions such as “what to consider when buying headphones?”, “what to consider when detailing my car at home?”, or “what are clean beauty products?” and receive helpful information to guide their shopping mission.
• Shop by occasion or purpose: Customers can search for and discover products based on activity, event, purpose, and other specific use cases by asking a range of questions such as “what do I need for cold weather golf?” or “I want to start an indoor garden.” Rufus suggests shoppable product categories—from golf base layers, jackets, and gloves to seed starters, potting mix, and grow lights—and related questions that customers can click on to conduct more specific searches.
• Get help comparing product categories: Customers can now ask “what’s the difference between lip gloss and lip oil?” or “compare drip to pour-over coffee makers” so they can find the type of product that best suits their needs and make even more confident purchase decisions.
• Find the best recommendations: Customers can ask for recommendations for exactly what they need, such as “what are good gifts for Valentine’s Day?” or “best dinosaur toys for a 5-year-old.” Rufus generates results tailored to the specific question and makes it quick and easy for customers to browse more refined results.
• Ask questions about a specific product while on a product detail page: Customers can use Rufus to quickly get answers to specific questions about individual products when they are viewing the product’s detail page, such as “is this pickleball paddle good for beginners?”, or “is this jacket machine washable?”, or “is this cordless drill easy to hold?”. Rufus will generate answers based on listing details, customer reviews, and community Q&As.”

IBL News | New York

OpenAI plans to sell existing shares in a tender offer led by venture firm Thrive Capital, in a deal that values the San Francisco-based company at $80 million, tripling its valuation in less than ten months, The New York Times reported.

Under this deal, employees will be able to cash out their shares.

Early last year, the venture capital firms Thrive Capital, Sequoia Capital, Andreessen Horowitz, and K2 Global agreed to buy OpenAI shares in a tender offer, valuing the company at around $29 billion.