J.P. Morgan Healthcare Conference—NVIDIA today announced new partnerships to transform the $10 trillion healthcare and life sciences industry by accelerating drug discovery, enhancing genomic research and pioneering advanced healthcare services with agentic and generative AI.
The convergence of AI, accelerated computing and biological data is turning healthcare into the largest technology industry. Healthcare leaders IQVIA, Illumina and Mayo Clinic, as well as Arc Institute, are using the latest NVIDIA technologies to develop solutions that will help advance human health.
These solutions include AI agents that can speed clinical trials by reducing administrative burden, AI models that learn from biology instruments to advance drug discovery and digital pathology, and physical AI robots for surgery, patient monitoring and operations. AI agents, AI instruments and AI robots will help address the $3 trillion of operations dedicated to supporting industry growth and create an AI factory opportunity in the hundreds of billions of dollars.
True progress in transforming health care will require solutions across the political, scientific and medical sectors. But new forms of artificial intelligence have the potential to help. Innovators are racing to deploy AI technologies to make health care more effective, equitable and humane.
AI could spot cancer early, design lifesaving drugs, assist doctors in surgery and even peer into people’s futures to predict and prevent disease. The potential to help people live longer, healthier lives is vast. But physicians and researchers must overcome a legion of challenges to harness AI’s potential.
The U.S. Department of Health and Human Services has issued its HHS Artificial Intelligence Strategic Plan, which the agency says will “set in motion a coordinated public-private approach to improving the quality, safety, efficiency, accessibility, equitability and outcomes in health and human services through the innovative, safe, and responsible use of AI.”
How Journalism Will Adapt in the Age of AI— from bloomberg.com/ by John Micklethwait The news business is facing its next enormous challenge. Here are eight reasons to be both optimistic and paranoid.
AI promises to get under the hood of our industry — to change the way we write and edit stories. It will challenge us, just like it is challenging other knowledge workers like lawyers, scriptwriters and accountants.
…
Most journalists love AI when it helps them uncover Iranian oil smuggling. Investigative journalism is not hard to sell to a newsroom. The second example is a little harder. Over the past month we have started testing AI-driven summaries for some longer stories on the Bloomberg Terminal.
The software reads the story and produces three bullet points. Customers like it — they can quickly see what any story is about. Journalists are more suspicious. Reporters worry that people will just read the summary rather than their story.
…
So, looking into our laboratory, what do I think will happen in the Age of AI? Here are eight predictions.
Nvidia’s CEO, Jensen Huang’s recent statement “IT will become the HR of AI agents” continues to spark debate about IT’s evolving role in managing AI systems. As AI tools become integral, IT teams will take on tasks like training and optimising AI agents, blending technical and HR responsibilities. So, how should organisations respond to this transformation?
At the end of 2024 and start of 2025, we’ve witnessed some fascinating developments in the world of AI and education, from from India’s emergence as a leader in AI education and Nvidia’s plans to build an AI school in Indonesia to Stanford’s Tutor CoPilot improving outcomes for underserved students.
Other highlights include Carnegie Learning partnering with AI for Education to train K-12 teachers, early adopters of AI sharing lessons about implementation challenges, and AI super users reshaping workplace practices through enhanced productivity and creativity.
India emerges as Global Leader in AI Education: Bosch Tech Compass 2025 — from medianews4u.com 57% Indians receive employer-provided AI training, surpassing Germany, and other European nations
Bengaluru: India is emerging as a global leader in artificial intelligence (AI) education, with over 50% of its population actively self-educating in AI-related skills, according to Bosch’s fourth annual Tech Compass Survey. The report highlights India’s readiness to embrace AI in work, education, and daily life, positioning the nation as a frontrunner in the AI revolution.
AI for Education reviewed the ElevenLabs AI Voice Tool through an educator lens, digging into the new autonomous voice agent functionality that facilitates interactive user engagement. We showcase the creation of a customized vocabulary bot, which defines words at a 9th-grade level and includes options for uploading supplementary material. The demo includes real-time testing of the bot’s capabilities in defining terms and quizzing users.
The discussion also explored the AI tool’s potential for aiding language learners and neurodivergent individuals, and Mandy presented a phone conversation coach bot to help her 13-year-old son, highlighting the tool’s ability to provide patient, repetitive practice opportunities.
While acknowledging the technology’s potential, particularly in accessibility and language learning, we also want to emphasize the importance of supervised use and privacy considerations. Right now the tool is currently free, this likely won’t always remain the case, so we encourage everyone to explore and test it out now as it continues to develop.
Why Combine Them? Faster Onboarding: Start broad with Deep Research, then refine and clarify concepts through Learn About. Finally, use NotebookLM to synthesize everything into a cohesive understanding.
Deeper Clarity: Unsure about a concept uncovered by Deep Research? Head to Learn About for a primer. Want to revisit key points later? Store them in NotebookLM and generate quick summaries on demand.
Adaptive Exploration: Create a feedback loop. Let new terms or angles from Learn About guide more targeted Deep Research queries. Then, compile all findings in NotebookLM for future reference. .
There are several challenges to making policy that make institutions hesitant to or delay their ability to produce it. Policy (as opposed to guidance) is much more likely to include a mixture of IT, HR, and legal services. This means each of those entities has to wrap their heads around GenAI—not just for their areas but for the other relevant areas such as teaching & learning, research, and student support. This process can definitely extend the time it takes to figure out the right policy.
That’s naturally true with every policy. It does not often come fast enough and is often more reactive than proactive.
Still, in my conversations and observations, the delay derives from three additional intersecting elements that feel like they all need to be in lockstep in order to actually take advantage of whatever possibilities GenAI has to offer.
Which Tool(s) To Use
Training, Support, & Guidance, Oh My!
Strategy: Setting a Direction…
Prophecies of the Flood — from oneusefulthing.org by Ethan Mollick What to make of the statements of the AI labs?
What concerns me most isn’t whether the labs are right about this timeline – it’s that we’re not adequately preparing for what even current levels of AI can do, let alone the chance that they might be correct. While AI researchers are focused on alignment, ensuring AI systems act ethically and responsibly, far fewer voices are trying to envision and articulate what a world awash in artificial intelligence might actually look like. This isn’t just about the technology itself; it’s about how we choose to shape and deploy it. These aren’t questions that AI developers alone can or should answer. They’re questions that demand attention from organizational leaders who will need to navigate this transition, from employees whose work lives may transform, and from stakeholders whose futures may depend on these decisions. The flood of intelligence that may be coming isn’t inherently good or bad – but how we prepare for it, how we adapt to it, and most importantly, how we choose to use it, will determine whether it becomes a force for progress or disruption. The time to start having these conversations isn’t after the water starts rising – it’s now.
Top AI Tools of 2024 — from ai-supremacy.com by Michael Spencer (behind a paywall) Which AI tools stood out for me in 2024? My list.
Memorable AI Tools of 2024
Catergories included:
Useful
Popular
Captures the zeighest of AI product innovation
Fun to try
Personally satisfying
NotebookLM
Perplexity
Claude
…
New “best” AI tool? Really? — from theneurondaily.com by Noah and Grant
PLUS: A free workaround to the “best” new AI…
What is Google’s Deep Research tool, and is it really “the best” AI research tool out there? … Here’s how it works: Think of Deep Research as a research team that can simultaneously analyze 50+ websites, compile findings, and create comprehensive reports—complete with citations.
Unlike asking ChatGPT to research for you, Deep Research shows you its research plan before executing, letting you edit the approach to get exactly what you need.
…
It’s currently free for the first month (though it’ll eventually be $20/month) when bundled with Gemini Advanced. Then again, Perplexity is always free…just saying.
We couldn’t just take J-Cal’s word for it, so we rounded up some other takes:
Our take: We then compared Perplexity, ChatGPT Search, and Deep Research (which we’re calling DR, or “The Docta” for short) on robot capabilities from CES revealed:
An excerpt from today’s Morning Edition from Bloomberg
Global banks will cut as many as 200,000 jobs in the next three to five years—a net 3% of the workforce—as AI takes on more tasks, according to a Bloomberg Intelligence survey. Back, middle office and operations are most at risk. A reminder that Citi said last year that AI is likely to replace more jobs in banking than in any other sector. JPMorgan had a more optimistic view (from an employee perspective, at any rate), saying its AI rollout has augmented, not replaced, jobs so far.
NVIDIA’s Apple moment?! — from theneurondaily.com by Noah Edelman and Grant Harvey PLUS: How to level up your AI workflows for 2025…
NVIDIA wants to put an AI supercomputer on your desk (and it only costs $3,000). … And last night at CES 2025, Jensen Huang announced phase two of this plan: Project DIGITS, a $3K personal AI supercomputer that runs 200B parameter models from your desk. Guess we now know why Apple recently developed an NVIDIA allergy…
… But NVIDIA doesn’t just want its “Apple PC moment”… it also wants its OpenAI moment. NVIDIA also announced Cosmos, a platform for building physical AI (think: robots and self-driving cars)—which Jensen Huang calls “the ChatGPT moment for robotics.”
NVIDIA is bringing AI from the cloud to personal devices and enterprises, covering all computing needs from developers to ordinary users.
At CES 2025, which opened this morning, NVIDIA founder and CEO Jensen Huang delivered a milestone keynote speech, revealing the future of AI and computing. From the core token concept of generative AI to the launch of the new Blackwell architecture GPU, and the AI-driven digital future, this speech will profoundly impact the entire industry from a cross-disciplinary perspective.
From DSC: I’m posting this next item (involving Samsung) as it relates to how TVs continue to change within our living rooms. AI is finding its way into our TVs…the ramifications of this remain to be seen.
The Rundown: Samsung revealed its new “AI for All” tagline at CES 2025, introducing a comprehensive suite of new AI features and products across its entire ecosystem — including new AI-powered TVs, appliances, PCs, and more.
The details:
Vision AI brings features like real-time translation, the ability to adapt to user preferences, AI upscaling, and instant content summaries to Samsung TVs.
Several of Samsung’s new Smart TVs will also have Microsoft Copilot built in, while also teasing a potential AI partnership with Google.
Samsung also announced the new line of Galaxy Book5 AI PCs, with new capabilities like AI-powered search and photo editing.
AI is also being infused into Samsung’s laundry appliances, art frames, home security equipment, and other devices within its SmartThings ecosystem.
Why it matters: Samsung’s web of products are getting the AI treatment — and we’re about to be surrounded by AI-infused appliances in every aspect of our lives. The edge will be the ability to sync it all together under one central hub, which could position Samsung as the go-to for the inevitable transition from smart to AI-powered homes.
***
“Samsung sees TVs not as one-directional devices for passive consumption but as interactive, intelligent partners that adapt to your needs,” said SW Yong, President and Head of Visual Display Business at Samsung Electronics. “With Samsung Vision AI, we’re reimagining what screens can do, connecting entertainment, personalization, and lifestyle solutions into one seamless experience to simplify your life.” — from Samsung
The following framework I offer for defining, understanding, and preparing for agentic AI blends foundational work in computer science with insights from cognitive psychology and speculative philosophy. Each of the seven levels represents a step-change in technology, capability, and autonomy. The framework expresses increasing opportunities to innovate, thrive, and transform in a data-fueled and AI-driven digital economy.
The Rise of AI Agents and Data-Driven Decisions — from devprojournal.com by Mike Monocello Fueled by generative AI and machine learning advancements, we’re witnessing a paradigm shift in how businesses operate and make decisions.
AI Agents Enhance Generative AI’s Impact Burley Kawasaki, Global VP of Product Marketing and Strategy at Creatio, predicts a significant leap forward in generative AI. “In 2025, AI agents will take generative AI to the next level by moving beyond content creation to active participation in daily business operations,” he says. “These agents, capable of partial or full autonomy, will handle tasks like scheduling, lead qualification, and customer follow-ups, seamlessly integrating into workflows. Rather than replacing generative AI, they will enhance its utility by transforming insights into immediate, actionable outcomes.”
Everyone’s talking about the potential of AI agents in 2025 (and don’t get me wrong, it’s really significant), but there’s a crucial detail that keeps getting overlooked: the gap between current capabilities and practical reliability.
Here’s the reality check that most predictions miss: AI agents currently operate at about 80% accuracy (according to Microsoft’s AI CEO). Sounds impressive, right? But here’s the thing – for businesses and users to actually trust these systems with meaningful tasks, we need 99% reliability. That’s not just a 19% gap – it’s the difference between an interesting tech demo and a business-critical tool.
This matters because it completely changes how we should think about AI agents in 2025. While major players like Microsoft, Google, and Amazon are pouring billions into development, they’re all facing the same fundamental challenge – making them work reliably enough that you can actually trust them with your business processes.
Think about it this way: Would you trust an assistant who gets things wrong 20% of the time? Probably not. But would you trust one who makes a mistake only 1% of the time, especially if they could handle repetitive tasks across your entire workflow? That’s a completely different conversation.
In the tech world, we like to label periods as the year of (insert milestone here). This past year (2024) was a year of broader experimentation in AI and, of course, agentic use cases.
As 2025 opens, VentureBeat spoke to industry analysts and IT decision-makers to see what the year might bring. For many, 2025 will be the year of agents, when all the pilot programs, experiments and new AI use cases converge into something resembling a return on investment.
In addition, the experts VentureBeat spoke to see 2025 as the year AI orchestration will play a bigger role in the enterprise. Organizations plan to make management of AI applications and agents much more straightforward.
Here are some themes we expect to see more in 2025.
AI agents take charge
Jérémy Grandillon, CEO of TC9 – AI Allbound Agency, said “Today, AI can do a lot, but we don’t trust it to take actions on our behalf. This will change in 2025. Be ready to ask your AI assistant to book a Uber ride for you.” Start small with one agent handling one task. Build up to an army.
“If 2024 was agents everywhere, then 2025 will be about bringing those agents together in networks and systems,” said Nicholas Holland, vice president of AI at Hubspot. “Micro agents working together to accomplish larger bodies of work, and marketplaces where humans can ‘hire’ agents to work alongside them in hybrid teams. Before long, we’ll be saying, ‘there’s an agent for that.'”
… Voice becomes default
Stop typing and start talking. Adam Biddlecombe, head of brand at Mindstream, predicts a shift in how we interact with AI. “2025 will be the year that people start talking with AI,” he said. “The majority of people interact with ChatGPT and other tools in the text format, and a lot of emphasis is put on prompting skills.
Biddlecombe believes, “With Apple’s ChatGPT integration for Siri, millions of people will start talking to ChatGPT. This will make AI so much more accessible and people will start to use it for very simple queries.”
Get ready for the next wave of advancements in AI. AGI arrives early, AI agents take charge, and voice becomes the norm. Video creation gets easy, AI embeds everywhere, and one-person billion-dollar companies emerge.
To better understand the types of roles that AI is impacting, ZoomInfo’s research team looked to its proprietary database of professional contacts for answers. The platform, which detects more than 1.5 million personnel changes per day, revealed a dramatic increase in AI-related job titles since 2022. With a 200% increase in two years, the data paints a vivid picture of how AI technology is reshaping the workforce.
Why does this shift in AI titles matter for every industry?
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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:
This is mind-blowing!
NVIDIA has introduced Edify 3D, a 3D AI generator that lets us create high-quality 3D scenes using just a simple prompt. And all the assets are fully editable!
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.
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.
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.
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.
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. 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.
We’ve added a new analysis tool. The tool helps Claude respond with mathematically precise and reproducible answers. You can then create interactive data visualizations with Artifacts.
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.
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.
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.
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.”
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.
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 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.
…
A major new analysisfrom 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.”
introducing swarm: an experimental framework for building, orchestrating, and deploying multi-agent systems. ?https://t.co/97n4fehmtM
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.
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%).
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.
“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.
Obviously this workflow works just as well for meetings as it does for lectures. Stay present in the meeting with no screens and just write down the key points with pen and paper. Then let NotebookLM assemble the detailed summary based on your high-level notes. https://t.co/fZMG7LgsWG
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 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
Advanced Voice is rolling out to all Plus and Team users in the ChatGPT app over the course of the week.
While you’ve been patiently waiting, we’ve added Custom Instructions, Memory, five new voices, and improved accents.
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.
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.
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!
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.
