Introducing Gemini 2.0: our new AI model for the agentic era — from blog.google by Sundar Pichai, Demis Hassabis, and Koray Kavukcuoglu

Today we’re excited to launch our next era of models built for this new agentic era: introducing Gemini 2.0, our most capable model yet. With new advances in multimodality — like native image and audio output — and native tool use, it will enable us to build new AI agents that bring us closer to our vision of a universal assistant.

We’re getting 2.0 into the hands of developers and trusted testers today. And we’re working quickly to get it into our products, leading with Gemini and Search. Starting today our Gemini 2.0 Flash experimental model will be available to all Gemini users. We’re also launching a new feature called Deep Research, which uses advanced reasoning and long context capabilities to act as a research assistant, exploring complex topics and compiling reports on your behalf. It’s available in Gemini Advanced today.

Over the last year, we have been investing in developing more agentic models, meaning they can understand more about the world around you, think multiple steps ahead, and take action on your behalf, with your supervision.

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Try Deep Research and our new experimental model in Gemini, your AI assistant — from blog.google by Dave Citron
Deep Research rolls out to Gemini Advanced subscribers today, saving you hours of time. Plus, you can now try out a chat optimized version of 2.0 Flash Experimental in Gemini on the web.

Today, we’re sharing the latest updates to Gemini, your AI assistant, including Deep Research — our new agentic feature in Gemini Advanced — and access to try Gemini 2.0 Flash, our latest experimental model.

Deep Research uses AI to explore complex topics on your behalf and provide you with findings in a comprehensive, easy-to-read report, and is a first look at how Gemini is getting even better at tackling complex tasks to save you time.1


Google Unveils A.I. Agent That Can Use Websites on Its Own — from nytimes.com by Cade Metz and Nico Grant (NOTE: This is a GIFTED article for/to you.)
The experimental tool can browse spreadsheets, shopping sites and other services, before taking action on behalf of the computer user.

Google on Wednesday unveiled a prototype of this technology, which artificial intelligence researchers call an A.I. agent.

Google’s new prototype, called Mariner, is based on Gemini 2.0, which the company also unveiled on Wednesday. Gemini is the core technology that underpins many of the company’s A.I. products and research experiments. Versions of the system will power the company’s chatbot of the same name and A.I. Overviews, a Google search tool that directly answers user questions.


Gemini 2.0 is the next chapter for Google AI — from axios.com by Ina Fried

Google Gemini 2.0 — a major upgrade to the core workings of Google’s AI that the company launched Wednesday — is designed to help generative AI move from answering users’ questions to taking action on its own…

The big picture: Hassabis said building AI systems that can take action on their own has been DeepMind’s focus since its early days teaching computers to play games such as chess and Go.

  • “We were always working towards agent-based systems,” Hassabis said. “From the beginning, they were able to plan and then carry out actions and achieve objectives.”
  • Hassabis said AI systems that can act as semi-autonomous agents also represent an important intermediate step on the path toward artificial general intelligence (AGI) — AI that can match or surpass human capabilities.
  • “If we think about the path to AGI, then obviously you need a system that can reason, break down problems and carry out actions in the world,” he said.

AI Agents vs. AI Assistants: Know the Key Differences — from aithority.com by Rishika Patel

The same paradigm applies to AI systems. AI assistants function as reactive tools, completing tasks like answering queries or managing workflows upon request. Think of chatbots or scheduling tools. AI agents, however, work autonomously to achieve set objectives, making decisions and executing tasks dynamically, adapting as new information becomes available.

Together, AI assistants and agents can enhance productivity and innovation in business environments. While assistants handle routine tasks, agents can drive strategic initiatives and problem-solving. This powerful combination has the potential to elevate organizations, making processes more efficient and professionals more effective.


Discover how to accelerate AI transformation with NVIDIA and Microsoft — from ignite.microsoft.com

Meet NVIDIA – The Engine of AI. From gaming to data science, self-driving cars to climate change, we’re tackling the world’s greatest challenges and transforming everyday life. The Microsoft and NVIDIA partnership enables Startups, ISVs, and Partners global access to the latest NVIDIA GPUs on-demand and comprehensive developer solutions to build, deploy and scale AI-enabled products and services.


Google + Meta + Apple New AI — from theneurondaily.com by Grant Harve

What else Google announced:

  • Deep Research: New feature that can explore topics and compile reports.
  • Project Astra: AI agent that can use Google Search, Lens, and Maps, understands multiple languages, and has 10-minute conversation memory.
  • Project Mariner: A browser control agent that can complete web tasks (83.5% success rate on WebVoyager benchmark). Read more about Mariner here.
  • Agents to help you play (or test) video games.

AI Agents: Easier To Build, Harder To Get Right — from forbes.com by Andres Zunino

The swift progress of artificial intelligence (AI) has simplified the creation and deployment of AI agents with the help of new tools and platforms. However, deploying these systems beneath the surface comes with hidden challenges, particularly concerning ethics, fairness and the potential for bias.

The history of AI agents highlights the growing need for expertise to fully realize their benefits while effectively minimizing risks.

 

Where to start with AI agents: An introduction for COOs — from fortune.com by Ganesh Ayyar

Picture your enterprise as a living ecosystem, where surging market demand instantly informs staffing decisions, where a new vendor’s onboarding optimizes your emissions metrics, where rising customer engagement reveals product opportunities. Now imagine if your systems could see these connections too! This is the promise of AI agents — an intelligent network that thinks, learns, and works across your entire enterprise.

Today, organizations operate in artificial silos. Tomorrow, they could be fluid and responsive. The transformation has already begun. The question is: will your company lead it?

The journey to agent-enabled operations starts with clarity on business objectives. Leaders should begin by mapping their business’s critical processes. The most pressing opportunities often lie where cross-functional handoffs create friction or where high-value activities are slowed by system fragmentation. These pain points become the natural starting points for your agent deployment strategy.


Create podcasts in minutes — from elevenlabs.io by Eleven Labs
Now anyone can be a podcast producer


Top AI tools for business — from theneuron.ai


This week in AI: 3D from images, video tools, and more — from heatherbcooper.substack.com by Heather Cooper
From 3D worlds to consistent characters, explore this week’s AI trends

Another busy AI news week, so I organized it into categories:

  • Image to 3D
  • AI Video
  • AI Image Models & Tools
  • AI Assistants / LLMs
  • AI Creative Workflow: Luma AI Boards

Want to speak Italian? Microsoft AI can make it sound like you do. — this is a gifted article from The Washington Post;
A new AI-powered interpreter is expected to simulate speakers’ voices in different languages during Microsoft Teams meetings.

Artificial intelligence has already proved that it can sound like a human, impersonate individuals and even produce recordings of someone speaking different languages. Now, a new feature from Microsoft will allow video meeting attendees to hear speakers “talk” in a different language with help from AI.


What Is Agentic AI?  — from blogs.nvidia.com by Erik Pounds
Agentic AI uses sophisticated reasoning and iterative planning to autonomously solve complex, multi-step problems.

The next frontier of artificial intelligence is agentic AI, which uses sophisticated reasoning and iterative planning to autonomously solve complex, multi-step problems. And it’s set to enhance productivity and operations across industries.

Agentic AI systems ingest vast amounts of data from multiple sources to independently analyze challenges, develop strategies and execute tasks like supply chain optimization, cybersecurity vulnerability analysis and helping doctors with time-consuming tasks.


 

2024-11-22: The Race to the TopDario Amodei on AGI, Risks, and the Future of Anthropic — from emergentbehavior.co by Prakash (Ate-a-Pi)

Risks on the Horizon: ASL Levels
The two key risks Dario is concerned about are:

a) cyber, bio, radiological, nuclear (CBRN)
b) model autonomy

These risks are captured in Anthropic’s framework for understanding AI Safety Levels (ASL):

1. ASL-1: Narrow-task AI like Deep Blue (no autonomy, minimal risk).
2. ASL-2: Current systems like ChatGPT/Claude, which lack autonomy and don’t pose significant risks beyond information already accessible via search engines.
3. ASL-3: Agents arriving soon (potentially next year) that can meaningfully assist non-state actors in dangerous activities like cyber or CBRN (chemical, biological, radiological, nuclear) attacks. Security and filtering are critical at this stage to prevent misuse.
4. ASL-4: AI smart enough to evade detection, deceive testers, and assist state actors with dangerous projects. AI will be strong enough that you would want to use the model to do anything dangerous. Mechanistic interpretability becomes crucial for verifying AI behavior.
5. ASL-5: AGI surpassing human intelligence in all domains, posing unprecedented challenges.

Anthropic’s if/then framework ensures proactive responses: if a model demonstrates danger, the team clamps down hard, enforcing strict controls.



Should You Still Learn to Code in an A.I. World? — from nytimes.com by
Coding boot camps once looked like the golden ticket to an economically secure future. But as that promise fades, what should you do? Keep learning, until further notice.

Compared with five years ago, the number of active job postings for software developers has dropped 56 percent, according to data compiled by CompTIA. For inexperienced developers, the plunge is an even worse 67 percent.
“I would say this is the worst environment for entry-level jobs in tech, period, that I’ve seen in 25 years,” said Venky Ganesan, a partner at the venture capital firm Menlo Ventures.

For years, the career advice from everyone who mattered — the Apple chief executive Tim Cook, your mother — was “learn to code.” It felt like an immutable equation: Coding skills + hard work = job.

Now the math doesn’t look so simple.

Also see:

AI builds apps in 2 mins flat — where the Neuron mentions this excerpt about Lovable:

There’s a new coding startup in town, and it just MIGHT have everybody else shaking in their boots (we’ll qualify that in a sec, don’t worry).

It’s called Lovable, the “world’s first AI fullstack engineer.”

Lovable does all of that by itself. Tell it what you want to build in plain English, and it creates everything you need. Want users to be able to log in? One click. Need to store data? One click. Want to accept payments? You get the idea.

Early users are backing up these claims. One person even launched a startup that made Product Hunt’s top 10 using just Lovable.

As for us, we made a Wordle clone in 2 minutes with one prompt. Only edit needed? More words in the dictionary. It’s like, really easy y’all.


When to chat with AI (and when to let it work) — from aiwithallie.beehiiv.com by Allie K. Miller

Re: some ideas on how to use Notebook LM:

  • Turn your company’s annual report into an engaging podcast
  • Create an interactive FAQ for your product manual
  • Generate a timeline of your industry’s history from multiple sources
  • Produce a study guide for your online course content
  • Develop a Q&A system for your company’s knowledge base
  • Synthesize research papers into digestible summaries
  • Create an executive content briefing from multiple competitor blog posts
  • Generate a podcast discussing the key points of a long-form research paper

Introducing conversation practice: AI-powered simulations to build soft skills — from codesignal.com by Albert Sahakyan

From DSC:
I have to admit I’m a bit suspicious here, as the “conversation practice” product seems a bit too scripted at times, but I post it because the idea of using AI to practice soft skills development makes a great deal of sense:


 

Denmark’s Gefion: The AI supercomputer that puts society first — from blog.aiport.tech by Daniel Nest
Can it help us reimagine what “AI success” looks like?

In late October 2024, NVIDIA’s Jensen Huang and Denmark’s King Frederik X symbolically plugged in the country’s new AI supercomputer, Gefion.

  1. Societal impact vs. monetization
  2. Public-private cooperation vs. venture capital
  3. Powered by renewable energy
 

Miscommunication Leads AI-Based Hiring Tools Astray — from adigaskell.org

Nearly every Fortune 500 company now uses artificial intelligence (AI) to screen resumes and assess test scores to find the best talent. However, new research from the University of Florida suggests these AI tools might not be delivering the results hiring managers expect.

The problem stems from a simple miscommunication between humans and machines: AI thinks it’s picking someone to hire, but hiring managers only want a list of candidates to interview.

Without knowing about this next step, the AI might choose safe candidates. But if it knows there will be another round of screening, it might suggest different and potentially stronger candidates.


AI agents explained: Why OpenAI, Google and Microsoft are building smarter AI agents — from digit.in by Jayesh Shinde

In the last two years, the world has seen a lot of breakneck advancement in the Generative AI space, right from text-to-text, text-to-image and text-to-video based Generative AI capabilities. And all of that’s been nothing short of stepping stones for the next big AI breakthrough – AI agents. According to Bloomberg, OpenAI is preparing to launch its first autonomous AI agent, which is codenamed ‘Operator,’ as soon as in January 2025.

Apparently, this OpenAI agent – or Operator, as it’s codenamed – is designed to perform complex tasks independently. By understanding user commands through voice or text, this AI agent will seemingly do tasks related to controlling different applications in the computer, send an email, book flights, and no doubt other cool things. Stuff that ChatGPT, Copilot, Google Gemini or any other LLM-based chatbot just can’t do on its own.


2025: The year ‘invisible’ AI agents will integrate into enterprise hierarchies  — from venturebeat.com by Taryn Plumb

In the enterprise of the future, human workers are expected to work closely alongside sophisticated teams of AI agents.

According to McKinsey, generative AI and other technologies have the potential to automate 60 to 70% of employees’ work. And, already, an estimated one-third of American workers are using AI in the workplace — oftentimes unbeknownst to their employers.

However, experts predict that 2025 will be the year that these so-called “invisible” AI agents begin to come out of the shadows and take more of an active role in enterprise operations.

“Agents will likely fit into enterprise workflows much like specialized members of any given team,” said Naveen Rao, VP of AI at Databricks and founder and former CEO of MosaicAI.


State of AI Report 2024 Summary — from ai-supremacy.com by Michael Spencer
Part I, Consolidation, emergence and adoption. 


Which AI Image Model Is the Best Speller? Let’s Find Out! — from whytryai.com by Daniel Nest
I test 7 image models to find those that can actually write.

The contestants
I picked 7 participants for today’s challenge:

  1. DALL-E 3 by OpenAI (via Microsoft Designer)
  2. FLUX1.1 [pro] by Black Forest Labs (via Glif)
  3. Ideogram 2.0 by Ideogram (via Ideogram)
  4. Imagen 3 by Google (via Image FX)
  5. Midjourney 6.1 by Midjourney (via Midjourney)
  6. Recraft V3 by Recraft (via Recraft)
  7. Stable Diffusion 3.5 Large by Stability AI (via Hugging Face)

How to get started with AI agents (and do it right) — from venturebeat.com by Taryn Plumb

So how can enterprises choose when to adopt third-party models, open source tools or build custom, in-house fine-tuned models? Experts weigh in.


OpenAI, Google and Anthropic Are Struggling to Build More Advanced AI — from bloomberg.com (behind firewall)
Three of the leading artificial intelligence companies are seeing diminishing returns from their costly efforts to develop newer models.


OpenAI and others seek new path to smarter AI as current methods hit limitations — from reuters.com by Krystal Hu and Anna Tong

Summary

  • AI companies face delays and challenges with training new large language models
  • Some researchers are focusing on more time for inference in new models
  • Shift could impact AI arms race for resources like chips and energy

NVIDIA Advances Robot Learning and Humanoid Development With New AI and Simulation Tools — from blogs.nvidia.com by Spencer Huang
New Project GR00T workflows and AI world model development technologies to accelerate robot dexterity, control, manipulation and mobility.


How Generative AI is Revolutionizing Product Development — from intelligenthq.com

A recent report from McKinsey predicts that generative AI could unlock up to $2.6 to $4.4 annually trillion in value within product development and innovation across various industries. This staggering figure highlights just how significantly generative AI is set to transform the landscape of product development. Generative AI app development is driving innovation by using the power of advanced algorithms to generate new ideas, optimize designs, and personalize products at scale. It is also becoming a cornerstone of competitive advantage in today’s fast-paced market. As businesses look to stay ahead, understanding and integrating technologies like generative AI app development into product development processes is becoming more crucial than ever.


What are AI Agents: How To Create a Based AI Agent — from ccn.com by Lorena Nessi

Key Takeaways

  • AI agents handle complex, autonomous tasks beyond simple commands, showcasing advanced decision-making and adaptability.
  • The Based AI Agent template by Coinbase and Replit provides an easy starting point for developers to build blockchain-enabled AI agents.
  • AI based agents specifically integrate with blockchain, supporting crypto wallets and transactions.
  • Securing API keys in development is crucial to protect the agent from unauthorized access.

What are AI Agents and How Are They Used in Different Industries? — from rtinsights.com by Salvatore Salamone
AI agents enable companies to make smarter, faster, and more informed decisions. From predictive maintenance to real-time process optimization, these agents are delivering tangible benefits across industries.

 



Google’s worst nightmare just became reality — from aidisruptor.ai by Alex McFarland
OpenAI just launched an all-out assault on traditional search engines.

Google’s worst nightmare just became reality. OpenAI didn’t just add search to ChatGPT – they’ve launched an all-out assault on traditional search engines.

It’s the beginning of the end for search as we know it.

Let’s be clear about what’s happening: OpenAI is fundamentally changing how we’ll interact with information online. While Google has spent 25 years optimizing for ad revenue and delivering pages of blue links, OpenAI is building what users actually need – instant, synthesized answers from current sources.

The rollout is calculated and aggressive: ChatGPT Plus and Team subscribers get immediate access, followed by Enterprise and Education users in weeks, and free users in the coming months. This staged approach is about systematically dismantling Google’s search dominance.




Open for AI: India Tech Leaders Build AI Factories for Economic Transformation — from blogs.nvidia.com
Yotta Data Services, Tata Communications, E2E Networks and Netweb are among the providers building and offering NVIDIA-accelerated infrastructure and software, with deployments expected to double by year’s end.


 

Along these same lines, see:

Introducing computer use, a new Claude 3.5 Sonnet, and Claude 3.5 Haiku

We’re also introducing a groundbreaking new capability in public beta: computer use. Available today on the API, developers can direct Claude to use computers the way people do—by looking at a screen, moving a cursor, clicking buttons, and typing text. Claude 3.5 Sonnet is the first frontier AI model to offer computer use in public beta. At this stage, it is still experimental—at times cumbersome and error-prone. We’re releasing computer use early for feedback from developers, and expect the capability to improve rapidly over time.


ZombAIs: From Prompt Injection to C2 with Claude Computer Use — from embracethered.com by Johann Rehberger

A few days ago, Anthropic released Claude Computer Use, which is a model + code that allows Claude to control a computer. It takes screenshots to make decisions, can run bash commands and so forth.

It’s cool, but obviously very dangerous because of prompt injection. Claude Computer Use enables AI to run commands on machines autonomously, posing severe risks if exploited via prompt injection.

This blog post demonstrates that it’s possible to leverage prompt injection to achieve, old school, command and control (C2) when giving novel AI systems access to computers.

We discussed one way to get malware onto a Claude Computer Use host via prompt injection. There are countless others, like another way is to have Claude write the malware from scratch and compile it. Yes, it can write C code, compile and run it. There are many other options.

TrustNoAI.

And again, remember do not run unauthorized code on systems that you do not own or are authorized to operate on.

Also relevant here, see:


Perplexity Grows, GPT Traffic Surges, Gamma Dominates AI Presentations – The AI for Work Top 100: October 2024 — from flexos.work by Daan van Rossum
Perplexity continues to gain users despite recent controversies. Five out of six GPTs see traffic boosts. This month’s highest gainers including Gamma, Blackbox, Runway, and more.


Growing Up: Navigating Generative AI’s Early Years – AI Adoption Report — from ai.wharton.upenn.edu by  Jeremy Korst, Stefano Puntoni, & Mary Purk

From a survey with more than 800 senior business leaders, this report’s findings indicate that weekly usage of Gen AI has nearly doubled from 37% in 2023 to 72% in 2024, with significant growth in previously slower-adopting departments like Marketing and HR. Despite this increased usage, businesses still face challenges in determining the full impact and ROI of Gen AI. Sentiment reports indicate leaders have shifted from feelings of “curiosity” and “amazement” to more positive sentiments like “pleased” and “excited,” and concerns about AI replacing jobs have softened. Participants were full-time employees working in large commercial organizations with 1,000 or more employees.


Apple study exposes deep cracks in LLMs’ “reasoning” capabilities — from arstechnica.com by Kyle Orland
Irrelevant red herrings lead to “catastrophic” failure of logical inference.

For a while now, companies like OpenAI and Google have been touting advanced “reasoning” capabilities as the next big step in their latest artificial intelligence models. Now, though, a new study from six Apple engineers shows that the mathematical “reasoning” displayed by advanced large language models can be extremely brittle and unreliable in the face of seemingly trivial changes to common benchmark problems.

The fragility highlighted in these new results helps support previous research suggesting that LLMs use of probabilistic pattern matching is missing the formal understanding of underlying concepts needed for truly reliable mathematical reasoning capabilities. “Current LLMs are not capable of genuine logical reasoning,” the researchers hypothesize based on these results. “Instead, they attempt to replicate the reasoning steps observed in their training data.”


Google CEO says more than a quarter of the company’s new code is created by AI — from businessinsider.in by Hugh Langley

  • More than a quarter of new code at Google is made by AI and then checked by employees.
  • Google is doubling down on AI internally to make its business more efficient.

Top Generative AI Chatbots by Market Share – October 2024 


Bringing developer choice to Copilot with Anthropic’s Claude 3.5 Sonnet, Google’s Gemini 1.5 Pro, and OpenAI’s o1-preview — from github.blog

We are bringing developer choice to GitHub Copilot with Anthropic’s Claude 3.5 Sonnet, Google’s Gemini 1.5 Pro, and OpenAI’s o1-preview and o1-mini. These new models will be rolling out—first in Copilot Chat, with OpenAI o1-preview and o1-mini available now, Claude 3.5 Sonnet rolling out progressively over the next week, and Google’s Gemini 1.5 Pro in the coming weeks. From Copilot Workspace to multi-file editing to code review, security autofix, and the CLI, we will bring multi-model choice across many of GitHub Copilot’s surface areas and functions soon.

 

From DSC:
Great…we have another tool called Canvas. Or did you say Canva?

Introducing canvas — from OpenAI
A new way of working with ChatGPT to write and code

We’re introducing canvas, a new interface for working with ChatGPT on writing and coding projects that go beyond simple chat. Canvas opens in a separate window, allowing you and ChatGPT to collaborate on a project. This early beta introduces a new way of working together—not just through conversation, but by creating and refining ideas side by side.

Canvas was built with GPT-4o and can be manually selected in the model picker while in beta. Starting today we’re rolling out canvas to ChatGPT Plus and Team users globally. Enterprise and Edu users will get access next week. We also plan to make canvas available to all ChatGPT Free users when it’s out of beta.


Using AI to buy your home? These companies think it’s time you should — from usatoday.com by Andrea Riquier

The way Americans buy homes is changing dramatically.

New industry rules about how home buyers’ real estate agents get paid are prompting a reckoning among housing experts and the tech sector. Many house hunters who are already stretched thin by record-high home prices and closing costs must now decide whether, and how much, to pay an agent.

A 2-3% commission on the median home price of $416,700 could be well over $10,000, and in a world where consumers are accustomed to using technology for everything from taxes to tickets, many entrepreneurs see an opportunity to automate away the middleman, even as some consumer advocates say not so fast.


The State of AI Report 2024 — from nathanbenaich.substack.com by Nathan Benaich


The Great Mismatch — from the-job.beehiiv.com. by Paul Fain
Artificial intelligence could threaten millions of decent-paying jobs held by women without degrees.

Women in administrative and office roles may face the biggest AI automation risk, find Brookings researchers armed with data from OpenAI. Also, why Indiana could make the Swiss apprenticeship model work in this country, and how learners get disillusioned when a certificate doesn’t immediately lead to a good job.

major new analysis from the Brookings Institution, using OpenAI data, found that the most vulnerable workers don’t look like the rail and dockworkers who have recaptured the national spotlight. Nor are they the creatives—like Hollywood’s writers and actors—that many wealthier knowledge workers identify with. Rather, they’re predominantly women in the 19M office support and administrative jobs that make up the first rung of the middle class.

“Unfortunately the technology and automation risks facing women have been overlooked for a long time,” says Molly Kinder, a fellow at Brookings Metro and lead author of the new report. “Most of the popular and political attention to issues of automation and work centers on men in blue-collar roles. There is far less awareness about the (greater) risks to women in lower-middle-class roles.”



Is this how AI will transform the world over the next decade? — from futureofbeinghuman.com by Andrew Maynard
Anthropic’s CEO Dario Amodei has just published a radical vision of an AI-accelerated future. It’s audacious, compelling, and a must-read for anyone working at the intersection of AI and society.

But if Amodei’s essay is approached as a conversation starter rather than a manifesto — which I think it should be — it’s hard to see how it won’t lead to clearer thinking around how we successfully navigate the coming AI transition.

Given the scope of the paper, it’s hard to write a response to it that isn’t as long or longer as the original. Because of this, I’d strongly encourage anyone who’s looking at how AI might transform society to read the original — it’s well written, and easier to navigate than its length might suggest.

That said, I did want to pull out a few things that struck me as particularly relevant and important — especially within the context of navigating advanced technology transitions.

And speaking of that essay, here’s a summary from The Rundown AI:

Anthropic CEO Dario Amodei just published a lengthy essay outlining an optimistic vision for how AI could transform society within 5-10 years of achieving human-level capabilities, touching on longevity, politics, work, the economy, and more.

The details:

  • Amodei believes that by 2026, ‘powerful AI’ smarter than a Nobel Prize winner across fields, with agentic and all multimodal capabilities, will be possible.
  • He also predicted that AI could compress 100 years of scientific progress into 10 years, curing most diseases and doubling the human lifespan.
  • The essay argued AI could strengthen democracy by countering misinformation and providing tools to undermine authoritarian regimes.
  • The CEO acknowledged potential downsides, including job displacement — but believes new economic models will emerge to address this.
  • He envisions AI driving unprecedented economic growth but emphasizes ensuring AI’s benefits are broadly distributed.

Why it matters: 

  • As the CEO of what is seen as the ‘safety-focused’ AI lab, Amodei paints a utopia-level optimistic view of where AI will head over the next decade. This thought-provoking essay serves as both a roadmap for AI’s potential and a call to action to ensure the responsible development of technology.

AI in the Workplace: Answering 3 Big Questions — from gallup.com by Kate Den Houter

However, most workers remain unaware of these efforts. Only a third (33%) of all U.S. employees say their organization has begun integrating AI into their business practices, with the highest percentage in white-collar industries (44%).

White-collar workers are more likely to be using AI. White-collar workers are, by far, the most frequent users of AI in their roles. While 81% of employees in production/frontline industries say they never use AI, only 54% of white-collar workers say they never do and 15% report using AI weekly.

Most employees using AI use it for idea generation and task automation. Among employees who say they use AI, the most common uses are to generate ideas (41%), to consolidate information or data (39%), and to automate basic tasks (39%).


Nvidia Blackwell GPUs sold out for the next 12 months as AI market boom continues — from techspot.com by Skye Jacobs
Analysts expect Team Green to increase its already formidable market share

Selling like hotcakes: The extraordinary demand for Blackwell GPUs illustrates the need for robust, energy-efficient processors as companies race to implement more sophisticated AI models and applications. The coming months will be critical to Nvidia as the company works to ramp up production and meet the overwhelming requests for its latest product.


Here’s my AI toolkit — from wondertools.substack.com by Jeremy Caplan and Nikita Roy
How and why I use the AI tools I do — an audio conversation

1. What are two useful new ways to use AI?

  • AI-powered research: Type a detailed search query into Perplexity instead of Google to get a quick, actionable summary response with links to relevant information sources. Read more of my take on why Perplexity is so useful and how to use it.
  • Notes organization and analysis: Tools like NotebookLM, Claude Projects, and Mem can help you make sense of huge repositories of notes and documents. Query or summarize your own notes and surface novel connections between your ideas.
 

AI’s Trillion-Dollar Opportunity — from bain.com by David Crawford, Jue Wang, and Roy Singh
The market for AI products and services could reach between $780 billion and $990 billion by 2027.

At a Glance

  • The big cloud providers are the largest concentration of R&D, talent, and innovation today, pushing the boundaries of large models and advanced infrastructure.
  • Innovation with smaller models (open-source and proprietary), edge infrastructure, and commercial software is reaching enterprises, sovereigns, and research institutions.
  • Commercial software vendors are rapidly expanding their feature sets to provide the best use cases and leverage their data assets.

Accelerated market growth. Nvidia’s CEO, Jensen Huang, summed up the potential in the company’s Q3 2024 earnings call: “Generative AI is the largest TAM [total addressable market] expansion of software and hardware that we’ve seen in several decades.”


And on a somewhat related note (i.e., emerging technologies), also see the following two postings:

Surgical Robots: Current Uses and Future Expectations — from medicalfuturist.com by Pranavsingh Dhunnoo
As the term implies, a surgical robot is an assistive tool for performing surgical procedures. Such manoeuvres, also called robotic surgeries or robot-assisted surgery, usually involve a human surgeon controlling mechanical arms from a control centre.

Key Takeaways

  • Robots’ potentials have been a fascination for humans and have even led to a booming field of robot-assisted surgery.
  • Surgical robots assist surgeons in performing accurate, minimally invasive procedures that are beneficial for patients’ recovery.
  • The assistance of robots extend beyond incisions and includes laparoscopies, radiosurgeries and, in the future, a combination of artificial intelligence technologies to assist surgeons in their craft.

Proto hologram tech allows cancer patients to receive specialist care without traveling large distances — from inavateonthenet.net

“Working with the team from Proto to bring to life, what several years ago would have seemed impossible, is now going to allow West Cancer Center & Research Institute to pioneer options for patients to get highly specialized care without having to travel to large metro areas,” said West Cancer’s CEO, Mitch Graves.




Clone your voice in minutes: The AI trick 95% don’t know about — from aidisruptor.ai by Alex McFarland
Warning: May cause unexpected bouts of talking to yourself

Now that you’ve got your voice clone, what can you do with it?

  1. Content Creation:
    • Podcast Production: Record episodes in half the time. Your listeners won’t know the difference, but your schedule will thank you.
    • Audiobook Narration: Always wanted to narrate your own book? Now you can, without spending weeks in a recording studio.
    • YouTube Videos: Create voiceovers for your videos in multiple languages. World domination, here you come!
  2. Business Brilliance:
    • Customer Service: Personalized automated responses that actually sound personal.
    • Training Materials: Create engaging e-learning content in your own voice, minus the hours of recording.
    • Presentations: Never worry about losing your voice before a big presentation again. Your clone’s got your back.

185 real-world gen AI use cases from the world’s leading organizations — from blog.google by Brian Hall; via Daniel Nest’s Why Try AI

In a matter of months, organizations have gone from AI helping answer questions, to AI making predictions, to generative AI agents. What makes AI agents unique is that they can take actions to achieve specific goals, whether that’s guiding a shopper to the perfect pair of shoes, helping an employee looking for the right health benefits, or supporting nursing staff with smoother patient hand-offs during shifts changes.

In our work with customers, we keep hearing that their teams are increasingly focused on improving productivity, automating processes, and modernizing the customer experience. These aims are now being achieved through the AI agents they’re developing in six key areas: customer service; employee empowerment; code creation; data analysis; cybersecurity; and creative ideation and production.

Here’s a snapshot of how 185 of these industry leaders are putting AI to use today, creating real-world use cases that will transform tomorrow.


AI Data Drop: 3 Key Insights from Real-World Research on AI Usage — from microsoft.com; via Daniel Nest’s Why Try AI
One of the largest studies of Copilot usage—at nearly 60 companies—reveals how AI is changing the way we work.

  1. AI is starting to liberate people from email
  2. Meetings are becoming more about value creation
  3. People are co-creating more with AI—and with one another


*** Dharmesh has been working on creating agent.ai — a professional network for AI agents.***


Speaking of agents, also see:

Onboarding the AI workforce: How digital agents will redefine work itself — from venturebeat.com by Gary Grossman

AI in 2030: A transformative force

  1. AI agents are integral team members
  2. The emergence of digital humans
  3. AI-driven speech and conversational interfaces
  4. AI-enhanced decision-making and leadership
  5. Innovation and research powered by AI
  6. The changing nature of job roles and skills

AI Video Tools You Can Use Today — from heatherbcooper.substack.com by Heather Cooper
The latest AI video models that deliver results

AI video models are improving so quickly, I can barely keep up! I wrote about unreleased Adobe Firefly Video in the last issue, and we are no closer to public access to Sora.

No worries – we do have plenty of generative AI video tools we can use right now.

  • Kling AI launched its updated v1.5 and the quality of image or text to video is impressive.
  • Hailuo MiniMax text to video remains free to use for now, and it produces natural and photorealistic results (with watermarks).
  • Runway added the option to upload portrait aspect ratio images to generate vertical videos in Gen-3 Alpha & Turbo modes.
  • …plus several more

 

Why Jensen Huang and Marc Benioff see ‘gigantic’ opportunity for agentic AI — from venturebeat.com by Taryn Plumb

Going forward, the opportunity for AI agents will be “gigantic,” according to Nvidia founder and CEO Jensen Huang.

Already, progress is “spectacular and surprising,” with AI development moving faster and faster and the industry getting into the “flywheel zone” that technology needs to advance, Huang said in a fireside chat at Salesforce’s flagship event Dreamforce this week.

“This is an extraordinary time,” Huang said while on stage with Marc Benioff, Salesforce chair, CEO and co-founder. “In no time in history has technology moved faster than Moore’s Law. We’re moving way faster than Moore’s Law, are arguably reasonably Moore’s Law squared.”

“We’ll have agents working with agents, agents working with us,” said Huang.

 

One thing often happens at keynotes and conferences. It surprised me…. — from donaldclarkplanb.blogspot.com by Donald Clark

AI is welcomed by those with dyslexia, and other learning issues, helping to mitigate some of the challenges associated with reading, writing, and processing information. Those who want to ban AI want to destroy the very thing that has helped most on accessibility. Here are 10 ways dyslexics, and others with issues around text-based learning, can use AI to support their daily activities and learning.

    • Text-to-Speech & Speech-to-Text Tools…
    • Grammar and Spelling Assistants…
    • Comprehension Tools…
    • Visual and Multisensory Tools…
    • …and more

Let’s Make a Movie Teaser With AI — from whytryai.com by Daniel Nest
How to use free generative AI tools to make a teaser trailer.

Here are the steps and the free tools we can use for each.

  1. Brainstorm ideas & flesh out the concept.
    1. Claude 3.5 Sonnet
    2. Google Gemini 1.5 Pro
    3. …or any other free LLM
  2. Create starting frames for each scene.
    1. FLUX.1 Pro
    2. Ideogram
    3. …or any other free text-to-image model
  3. Bring the images to life.
    1. Kling AI
    2. Luma Dream Machine
    3. Runway Gen-2
  4. Generate the soundtrack.
    1. Udio
    2. Suno
  5. Add sound effects.
    1. ElevenLabs Sound Effects
    2. ElevenLabs VideoToSoundEffects
    3. Meta Audiobox
  6. Put everything together.
    1. Microsoft Clipchamp
    2. DaVinci Resolve
    3. …or any other free video editing tool.

Here we go.


Is AI in Schools Promising or Overhyped? Potentially Both, New Reports Suggest — from the74million.org by Greg Toppo; via Claire Zau
One urges educators to prep for an artificial intelligence boom. The other warns that it could all go awry. Together, they offer a reality check.

Are U.S. public schools lagging behind other countries like Singapore and South Korea in preparing teachers and students for the boom of generative artificial intelligence? Or are our educators bumbling into AI half-blind, putting students’ learning at risk?

Or is it, perhaps, both?

Two new reports, coincidentally released on the same day last week, offer markedly different visions of the emerging field: One argues that schools need forward-thinking policies for equitable distribution of AI across urban, suburban and rural communities. The other suggests they need something more basic: a bracing primer on what AI is and isn’t, what it’s good for and how it can all go horribly wrong.


Bite-Size AI Content for Faculty and Staff — from aiedusimplified.substack.com by Lance Eaton
Another two 5-tips videos for faculty and my latest use case: creating FAQs!

I had an opportunity recently to do more of my 15-minute lightning talks. You can see my lightning talks from late winter in this post, or can see all of them on my YouTube channel. These two talks were focused on faculty in particular.


Also from Lance, see:


AI in Education: Leading a Paradigm Shift — from gettingsmart.com by Dr. Tyler Thigpen

Despite possible drawbacks, an exciting wondering has been—What if AI was a tipping point helping us finally move away from a standardized, grade-locked, ranking-forced, batched-processing learning model based on the make believe idea of “the average man” to a learning model that meets every child where they are at and helps them grow from there?

I get that change is indescribably hard and there are risks. But the integration of AI in education isn’t a trend. It’s a paradigm shift that requires careful consideration, ongoing reflection, and a commitment to one’s core values. AI presents us with an opportunity—possibly an unprecedented one—to transform teaching and learning, making it more personalized, efficient, and impactful. How might we seize the opportunity boldly?


California and NVIDIA Partner to Bring AI to Schools, Workplaces — from govtech.com by Abby Sourwine
The latest step in Gov. Gavin Newsom’s plans to integrate AI into public operations across California is a partnership with NVIDIA intended to tailor college courses and professional development to industry needs.

California Gov. Gavin Newsom and tech company NVIDIA joined forces last week to bring generative AI (GenAI) to community colleges and public agencies across the state. The California Community Colleges Chancellor’s Office (CCCCO), NVIDIA and the governor all signed a memorandum of understanding (MOU) outlining how each partner can contribute to education and workforce development, with the goal of driving innovation across industries and boosting their economic growth.


Listen to anything on the go with the highest-quality voices — from elevenlabs.io; via The Neuron
The ElevenLabs Reader App narrates articles, PDFs, ePubs, newsletters, or any other text content. Simply choose a voice from our expansive library, upload your content, and listen on the go.

Per The Neuron

Some cool use cases:

  • Judy Garland can teach you biology while walking to class.
  • James Dean can narrate your steamy romance novel.
  • Sir Laurence Olivier can read you today’s newsletter—just paste the web link and enjoy!

Why it’s important: ElevenLabs shared how major Youtubers are using its dubbing services to expand their content into new regions with voices that actually sound like them (thanks to ElevenLabs’ ability to clone voices).
Oh, and BTW, it’s estimated that up to 20% of the population may have dyslexia. So providing people an option to listen to (instead of read) content, in their own language, wherever they go online can only help increase engagement and communication.


How Generative AI Improves Parent Engagement in K–12 Schools — from edtechmagazine.com by Alexadner Slagg
With its ability to automate and personalize communication, generative artificial intelligence is the ideal technological fix for strengthening parent involvement in students’ education.

As generative AI tools populate the education marketplace, the technology’s ability to automate complex, labor-intensive tasks and efficiently personalize communication may finally offer overwhelmed teachers a way to effectively improve parent engagement.

These personalized engagement activities for students and their families can include local events, certification classes and recommendations for books and videos. “Family Feed might suggest courses, such as an Adobe certification,” explains Jackson. “We have over 14,000 courses that we have vetted and can recommend. And we have books and video recommendations for students as well.”

Including personalized student information and an engagement opportunity makes it much easier for parents to directly participate in their children’s education.


Will AI Shrink Disparities in Schools, or Widen Them? — edsurge.com by Daniel Mollenkamp
Experts predict new tools could boost teaching efficiency — or create an “underclass of students” taught largely through screens.

 

From DSC:
The above item is simply excellent!!! I love it!



Also relevant/see:

3 new Chrome AI features for even more helpful browsing — from blog.google from Parisa Tabriz
See how Chrome’s new AI features, including Google Lens for desktop and Tab compare, can help you get things done more easily on the web.


On speaking to AI — from oneusefulthing.org by Ethan Mollick
Voice changes a lot of things

So, let’s talk about ChatGPT’s new Advanced Voice mode and the new AI-powered Siri. They are not just different approaches to talking to AI. In many ways, they represent the divide between two philosophies of AI – Copilots versus Agents, small models versus large ones, specialists versus generalists.


Your guide to AI – August 2024 — from nathanbenaich.substack.com by Nathan Benaich and Alex Chalmers


Microsoft says OpenAI is now a competitor in AI and search — from cnbc.com by Jordan Novet

Key Points

  • Microsoft’s annually updated list of competitors now includes OpenAI, a long-term strategic partner.
  • The change comes days after OpenAI announced a prototype of a search engine.
  • Microsoft has reportedly invested $13 billion into OpenAI.


Excerpt from by Graham Clay

1. Flux, an open-source text-to-image creator that is comparable to industry leaders like Midjourney, was released by Black Forest Labs (the “original team” behind Stable Diffusion). It is capable of generating high quality text in images (there are tons of educational use cases). You can play with it on their demo page, on Poe, or by running it on your own computer (tutorial here).

Other items re: Flux:

How to FLUX  — from heatherbcooper.substack.com by Heather Cooper
Where to use FLUX online & full tutorial to create a sleek ad in minutes

.

Also from Heather Cooper:

Introducing FLUX: Open-Source text to image model

FLUX… has been EVERYWHERE this week, as I’m sure you have seen. Developed by Black Forest Labs, is an open-source image generation model that’s gaining attention for its ability to rival leading models like Midjourney, DALL·E 3, and SDXL.

What sets FLUX apart is its blend of creative freedom, precision, and accessibility—it’s available across multiple platforms and can be run locally.

Why FLUX Matters
FLUX’s open-source nature makes it accessible to a broad audience, from hobbyists to professionals.

It offers advanced multimodal and parallel diffusion transformer technology, delivering high visual quality, strong prompt adherence, and diverse outputs.

It’s available in 3 models:
FLUX.1 [pro]: A high-performance, commercial image synthesis model.
FLUX.1 [dev]: An open-weight, non-commercial variant of FLUX.1 [pro]
FLUX.1 [schnell]: A faster, distilled version of FLUX.1, operating up to 10x quicker.

Daily Digest: Huge (in)Flux of AI videos. — from bensbites.beehiiv.com
PLUS: Review of ChatGPT’s advanced voice mode.

  1. During the weekend, image models made a comeback. Recently released Flux models can create realistic images with near-perfect text—straight from the model, without much patchwork. To get the party going, people are putting these images into video generation models to create prettytrippyvideos. I can’t identify half of them as AI, and they’ll only get better. See this tutorial on how to create a video ad for your product..

 


7 not only cool but handy use cases of new Claude — from techthatmatters.beehiiv.com by Harsh Makadia

  1. Data visualization
  2. Infographic
  3. Copy the UI of a website
  4. …and more

Achieving Human Level Competitive Robot Table Tennis — from sites.google.com

 

Per the Rundown AI:

Why it matters: AI is slowly shifting from a tool we text/prompt with, to an intelligence that we collaborate, learn, and grow with. Advanced Voice Mode’s ability to understand and respond to emotions in real-time convos could also have huge use cases in everything from customer service to mental health support.

Also relevant/see:


Creators to Have Personalized AI Assistants, Meta CEO Mark Zuckerberg Tells NVIDIA CEO Jensen Huang — from blogs.nvidia.com by Brian Caulfield
Zuckerberg and Huang explore the transformative potential of open source AI, the launch of AI Studio, and exchange leather jackets at SIGGRAPH 2024.

“Every single restaurant, every single website will probably, in the future, have these AIs …” Huang said.

“…just like every business has an email address and a website and a social media account, I think, in the future, every business is going to have an AI,” Zuckerberg responded.

More broadly, the advancement of AI across a broad ecosystem promises to supercharge human productivity, for example, by giving every human on earth a digital assistant — or assistants — allowing people to live richer lives that they can interact with quickly and fluidly.

Also related/see:


From DSC:
Today was a MUCH better day for Nvidia however (up 12.81%). But it’s been very volatile in the last several weeks — as people and institutions ask where the ROI’s are going to come from.






9 compelling reasons to learn how to use AI Chatbots — from interestingengineering.com by Atharva Gosavi
AI Chatbots are conversational agents that can act on your behalf and converse with humans – a futuristic novelty that is already getting people excited about its usage in improving efficiency.

7. Accessibility and inclusivity
Chatbots can be designed to support multiple languages and accessibility needs, making services more inclusive. They can cater to users with disabilities by providing voice interaction capabilities and simplifying access to information. Understanding how to develop inclusive chatbots can help you contribute to making technology more accessible to everyone, a crucial aspect in today’s diverse society.

8. Future-proofing your skills
AI and automation are the future of work. Having the skills of building AI chatbots is a great way to future-proof your skills, and given the rising trajectory of AI, it’ll be a demanding skill in the market in the years to come. Staying ahead of technological trends is a great way to ensure you remain relevant and competitive in the job market.


Top 7 generative AI use cases for business — from cio.com by Grant Gross
Advanced chatbots, digital assistants, and coding helpers seem to be some of the sweet spots for gen AI use so far in business.

Many AI experts say the current use cases for generative AI are just the tip of the iceberg. More uses cases will present themselves as gen AIs get more powerful and users get more creative with their experiments.

However, a handful of gen AI use cases are already bubbling up. Here’s a look at the most popular and promising.

 


“Who to follow in AI” in 2024? [Part I] — from ai-supremacy.com by Michael Spencer [some of posting is behind a paywall]
#1-20 [of 150] – I combed the internet, I found the best sources of AI insights, education and articles. LinkedIn | Newsletters | X | YouTube | Substack | Threads | Podcasts

Also see:

Along these lines, also see:


AI In Medicine: 3 Future Scenarios From Utopia To Dystopia — from medicalfuturist.com by Andrea Koncz
There’s a vast difference between baseless fantasizing and realistic forward planning. Structured methodologies help us learn how to “dream well”.

Key Takeaways

  • We’re often told that daydreaming and envisioning the future is a waste of time. But this notion is misguided.
  • We all instinctively plan for the future in small ways, like organizing a trip or preparing for a dinner party. This same principle can be applied to larger-scale issues, and smart planning does bring better results.
  • We show you a method that allows us to think “well” about the future on a larger scale so that it better meets our needs.

Adobe Unveils Powerful New Innovations in Illustrator and Photoshop Unlocking New Design Possibilities for Creative Pros — from news.adobe.com

  • Latest Illustrator and Photoshop releases accelerate creative workflows, save pros time and empower designers to realize their visions faster
  • New Firefly-enabled features like Generative Shape Fill in Illustrator along with the Dimension Tool, Mockup, Text to Pattern, the Contextual Taskbar and performance enhancement tools accelerate productivity and free up time so creative pros can dive deeper into the parts of their work they love
  • Photoshop introduces all-new Selection Brush Tool and the general availability of Generate Image, Adjustment Brush Tool and other workflow enhancements empowering creators to make complex edits and unique designs
    .


Nike is using AI to turn athletes’ dreams into shoes — from axios.com by Ina Fried

Zoom in: Nike used genAI for ideation, including using a variety of prompts to produce images with different textures, materials and color to kick off the design process.

What they’re saying: “It’s a new way for us to work,” Nike lead footwear designer Juliana Sagat told Axios during a media tour of the showcase on Tuesday.
.


AI meets ‘Do no harm’: Healthcare grapples with tech promises — from finance.yahoo.com by Maya Benjamin

Major companies are moving at high speed to capture the promises of artificial intelligence in healthcare while doctors and experts attempt to integrate the technology safely into patient care.

“Healthcare is probably the most impactful utility of generative AI that there will be,” Kimberly Powell, vice president of healthcare at AI hardware giant Nvidia (NVDA), which has partnered with Roche’s Genentech (RHHBY) to enhance drug discovery in the pharmaceutical industry, among other investments in healthcare companies, declared at the company’s AI Summit in June.


Mistral reignites this week’s LLM rivalry with Large 2 (source) — from superhuman.ai

Today, we are announcing Mistral Large 2, the new generation of our flagship model. Compared to its predecessor, Mistral Large 2 is significantly more capable in code generation, mathematics, and reasoning. It also provides a much stronger multilingual support, and advanced function calling capabilities.


Meta releases the biggest and best open-source AI model yet — from theverge.com by Alex Heath
Llama 3.1 outperforms OpenAI and other rivals on certain benchmarks. Now, Mark Zuckerberg expects Meta’s AI assistant to surpass ChatGPT’s usage in the coming months.

Back in April, Meta teased that it was working on a first for the AI industry: an open-source model with performance that matched the best private models from companies like OpenAI.

Today, that model has arrived. Meta is releasing Llama 3.1, the largest-ever open-source AI model, which the company claims outperforms GPT-4o and Anthropic’s Claude 3.5 Sonnet on several benchmarks. It’s also making the Llama-based Meta AI assistant available in more countries and languages while adding a feature that can generate images based on someone’s specific likeness. CEO Mark Zuckerberg now predicts that Meta AI will be the most widely used assistant by the end of this year, surpassing ChatGPT.


4 ways to boost ChatGPT — from wondertools.substack.com by Jeremy Caplan & The PyCoach
Simple tactics for getting useful responses

To help you make the most of ChatGPT, I’ve invited & edited today’s guest post from the author of a smart AI newsletter called The Artificial Corner. I appreciate how Frank Andrade pushes ChatGPT to produce better results with four simple, clever tactics. He offers practical examples to help us all use AI more effectively.

Frank Andrade: Most of us fail to make the most of ChatGPT.

  1. We omit examples in our prompts.
  2. We fail to assign roles to ChatGPT to guide its behavior.
  3. We let ChatGPT guess instead of providing it with clear guidance.

If you rely on vague prompts, learning how to create high-quality instructions will get you better results. It’s a skill often referred to as prompt engineering. Here are several techniques to get you to the next level.

 

How to use Perplexity in your daily workflow — from ai-supremacy.com by Michael Spencer and Alex McFarland
“I barely use Google anymore (for anything)” says today’s guest author.

Make Perplexity your go-to research companion with these strategies:

  • Morning briefings: Start your day by asking Perplexity for the latest news in your field. (I personally like to use Perplexity to curate the top AI news of the day to consider writing about for Unite AI and Techopedia.)
  • Fact-checking: Use it to quickly verify information before including it in your work.
  • Brainstorming: Generate ideas for projects or content by asking open-ended questions.
  • Learning new concepts: When you encounter an unfamiliar term or idea, turn to Perplexity for a quick, comprehensive explanation.
  • Writing assistance: Use it to find relevant statistics, examples, or counterarguments for your content.

From DSC:
So I used it to ask “What is Elon Musk’s Memphis Supercluster?” (which went online yesterday I believe) — which resulted in this reply:

Elon Musk’s Memphis Supercluster is a newly activated AI training cluster that is claimed to be the most powerful in the world. Here are the key details about this supercomputer:

1. Location: The supercluster is located in Memphis, Tennessee[1][2].

2. Hardware: It consists of 100,000 liquid-cooled Nvidia H100 GPUs connected through a single RDMA (Remote Direct Memory Access) fabric[1][3].

3. Purpose: The supercluster is designed for training large language models (LLMs) and other advanced AI technologies for Musk’s xAI company[1][2].

4. Activation: The Memphis Supercluster began training at approximately 4:20 AM local time on July 22, 2024[1][3].

5. Collaboration: The project is a result of collaboration between xAI, X (formerly Twitter), Nvidia, and other supporting companies[1][2].

6. Investment: With each H100 GPU estimated to cost between $30,000 to $40,000, the total investment in GPUs alone is estimated to be between $3 billion to $4 billion[5].

7. Goals: Musk claims that this supercluster will be used to develop “the world’s most powerful AI by every measure” by December 2024[1].

8. Comparison: The Memphis Supercluster’s 100,000 H100 GPUs significantly outclass other supercomputers in terms of GPU horsepower, such as Frontier (37,888 AMD GPUs) and Microsoft Eagle (14,400 Nvidia H100 GPUs)[3].

9. Infrastructure: The project required significant infrastructure development, including fiber optic networking[5].

While Musk’s claims about the supercluster’s capabilities are ambitious, it remains to be seen how it will perform in practice and whether it will meet the stated goals within the given timeframe[1].

Citations:
[1] https://venturebeat.com/ai/elon-musk-announces-most-powerful-ai-training-cluster-in-the-world/
[2] https://www.tuaw.com/2024/07/22/elon-musks-xai-unveils-worlds-most-powerful-ai-training-cluster/
[3] https://www.tomshardware.com/pc-components/gpus/elon-musk-fires-up-the-most-powerful-ai-training-cluster-in-the-world-uses-100000-nvidia-h100-gpus-on-a-single-fabric
[4] https://www.thestack.technology/xai-elon-musk-ai-supercomputer/
[5] https://www.benzinga.com/news/24/07/39881748/elon-musks-xai-flips-the-switch-on-100k-nvidia-h100-gpus-worth-up-to-4b-in-memphis-supercluster-most
[6] https://www.youtube.com/watch?v=0JhtJa05C2Y

—–
Elon’s AI empire expands — from theneurondaily.com by Grant Harvey
Elon Musk’s team at xAI just powered on the “World’s Most Powerful AI Training Cluster.”
If you don’t know what a supercluster is, it’s basically a massive network of Nvidia GPUs (computer chips) working together as a single unit to solve “super” complex calculations at unprecedented speeds.

And this Memphis Supercluster is the most “super” supercluster we’ve ever seen. The new facility, dubbed the “Gigafactory of Compute”, is a beast:

  • 100,000 liquid-cooled Nvidia H100 GPUs on a single RDMA fabric (for context, Google snagged only 50,000 H100 GPUs last year).
  • Up to 150 megawatts of electricity usage per hour—enough for 100K homes.
  • At least one million gallons of water per day to keep cool!

What to expect: Better models, more frequently. That’s been the trend, at least—look at how the last few model releases have become more squished together. 


OpenAI to make GPT-4o Advanced Voice available by the end of the month to select group of users — from tomsguide.com by Ryan Morrison

GPT-4o Advanced Voice is an entirely new type of voice assistant, similar to but larger than the recently unveiled French model Moshi, which argued with me over a story.

In demos of the model, we’ve seen GPT-4o Advanced Voice create custom character voices, generate sound effects while telling a story and even act as a live translator.

This native speech ability is a significant step in creating more natural AI assistants. In the future, it will also come with live vision abilities, allowing the AI to see what you see.


Could AGI break the world? — from theneurondaily.com by Noah Edelman

“Biggest IT outage in history” proves we’re not ready for AGI.

Here’s the TL;DR
—a faulty software update from cybersecurity firm Crowdstrike made this happen:

  • Grounded 5,000+ flights around the world.
  • Slowed healthcare across the UK.
  • Forced retailers to revert to cash-only transactions in Australia (what is this, the stone ages?!).


Here’s where AI comes in: Imagine today’s AI as a new operating system. In 5-10 years, it’ll likely be as integrated into our economy as Microsoft’s cloud servers are now. This isn’t that far-fetched—Microsoft is already planning to embed AI into all its programs.

So what if a Crowdstrike-like incident happens with a more powerful AI system? Some experts predict an AI-powered IT outage could be 10x worse than Friday’s fiasco.


The Crowdstrike outage and global software’s single-point failure problem — from cnbc.com by Kaya Ginsky

KEY POINTS

  • The CrowdStrike software bug that took down global IT infrastructure exposed a single-point-of-failure risk unrelated to malicious cyberattack.
  • National and cybersecurity experts say the risk of this kind of technical outage is increasing alongside the risk of hacks, and the market will need to adopt better competitive practices.
  • Government is also likely to look at new regulations related to software updates and patches.

The “largest IT outage in history,” briefly explained — from vox.com by Li Zhou
Airlines, banks, and hospitals saw computer systems go down because of a CrowdStrike software glitch.

 
© 2024 | Daniel Christian