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.
Per The Rundown: OpenAI just launched a surprising new way to access ChatGPT — through an old-school 1-800 number & also rolled out a new WhatsApp integration for global users during Day 10 of the company’s livestream event.
Agentic AI represents a significant evolution in artificial intelligence, offering enhanced autonomy and decision-making capabilities beyond traditional AI systems. Unlike conventional AI, which requires human instructions, agentic AI can independently perform complex tasks, adapt to changing environments, and pursue goals with minimal human intervention.
This makes it a powerful tool across various industries, especially in the customer service function. To understand it better, let’s compare AI Agents with non-AI agents.
… Characteristics of Agentic AI
Autonomy: Achieves complex objectives without requiring human collaboration.
Language Comprehension: Understands nuanced human speech and text effectively.
Rationality: Makes informed, contextual decisions using advanced reasoning engines.
Adaptation: Adjusts plans and goals in dynamic situations.
Workflow Optimization: Streamlines and organizes business workflows with minimal oversight.
How, then, can we research and observe how our systems are used while rigorously maintaining user privacy?
Claude insights and observations, or “Clio,” is our attempt to answer this question. Clio is an automated analysis tool that enables privacy-preserving analysis of real-world language model use. It gives us insights into the day-to-day uses of claude.ai in a way that’s analogous to tools like Google Trends. It’s also already helping us improve our safety measures. In this post—which accompanies a full research paper—we describe Clio and some of its initial results.
Evolving tools redefine AI video — from heatherbcooper.substack.com by Heather Cooper Google’s Veo 2, Kling 1.6, Pika 2.0 & more
AI video continues to surpass expectations
The AI video generation space has evolved dramatically in recent weeks, with several major players introducing groundbreaking tools.
Here’s a comprehensive look at the current landscape:
Veo 2…
Pika 2.0…
Runway’s Gen-3…
Luma AI Dream Machine…
Hailuo’s MiniMax…
OpenAI’s Sora…
Hunyuan Video by Tencent…
There are several other video models and platforms, including …
When it comes to classroom edtech use, digital tools have a drastically different impact when they are used actively instead of passively–a critical difference examined in the 2023-2024 Speak Up Research by Project Tomorrow.
Students also outlined their ideal active learning technologies:
2024: The State of Generative AI in the Enterprise — from menlovc.com (Menlo Ventures) The enterprise AI landscape is being rewritten in real time. As pilots give way to production, we surveyed 600 U.S. enterprise IT decision-makers to reveal the emerging winners and losers.
This spike in spending reflects a wave of organizational optimism; 72% of decision-makers anticipate broader adoption of generative AI tools in the near future. This confidence isn’t just speculative—generative AI tools are already deeply embedded in the daily work of professionals, from programmers to healthcare providers.
Despite this positive outlook and increasing investment, many decision-makers are still figuring out what will and won’t work for their businesses. More than a third of our survey respondents do not have a clear vision for how generative AI will be implemented across their organizations. This doesn’t mean they’re investing without direction; it simply underscores that we’re still in the early stages of a large-scale transformation. Enterprise leaders are just beginning to grasp the profound impact generative AI will have on their organizations.
Business spending on generative AI surged 500% this year, hitting $13.8 billion — up from just $2.3 billion in 2023, according to data from Menlo Ventures released Wednesday.
OpenAI ceded market share in enterprise AI, declining from 50% to 34%, per the report.
Amazon-backed Anthropic doubled its market share from 12% to 24%.
Microsoft has quietly built the largest enterprise AI agent ecosystem, with over 100,000 organizations creating or editing AI agents through its Copilot Studio since launch – a milestone that positions the company ahead in one of enterprise tech’s most closely watched and exciting segments.
…
The rapid adoption comes as Microsoft significantly expands its agent capabilities. At its Ignite conference [that started on 11/19/24], the company announced it will allow enterprises to use any of the 1,800 large language models (LLMs) in the Azure catalog within these agents – a significant move beyond its exclusive reliance on OpenAI’s models. The company also unveiled autonomous agents that can work independently, detecting events and orchestrating complex workflows with minimal human oversight.
To understand the implications of AI agents, it’s useful to clarify the distinctions between AI, generative AI, and AI agents and explore the opportunities and risks they present to our autonomy, relationships, and decision-making.
… AI Agents: These are specialized applications of AI designed to perform tasks or simulate interactions. AI agents can be categorized into:
Tool Agents…
Simulation Agents..
While generative AI creates outputs from prompts, AI agents use AI to act with intention, whether to assist (tool agents) or emulate (simulation agents). The latter’s ability to mirror human thought and action offers fascinating possibilities — and raises significant risks.
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.
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.
In a groundbreaking study, researchers from Penn Engineering showed how AI-powered robots can be manipulated to ignore safety protocols, allowing them to perform harmful actions despite normally rejecting dangerous task requests.
What did they find ?
Researchers found previously unknown security vulnerabilities in AI-governed robots and are working to address these issues to ensure the safe use of large language models(LLMs) in robotics.
Their newly developed algorithm, RoboPAIR, reportedly achieved a 100% jailbreak rate by bypassing the safety protocols on three different AI robotic systems in a few days.
Using RoboPAIR, researchers were able to manipulate test robots into performing harmful actions, like bomb detonation and blocking emergency exits, simply by changing how they phrased their commands.
Why does it matter?
This research highlights the importance of spotting weaknesses in AI systems to improve their safety, allowing us to test and train them to prevent potential harm.
From DSC: Great! Just what we wanted to hear. But does it surprise anyone? Even so…we move forward at warp speeds.
From DSC:
So, given the above item, does the next item make you a bit nervous as well? I saw someone on Twitter/X exclaim, “What could go wrong?” I can’t say I didn’t feel the same way.
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.
Per The Rundown AI:
The Rundown: Anthropic just introduced a new capability called ‘computer use’, alongside upgraded versions of its AI models, which enables Claude to interact with computers by viewing screens, typing, moving cursors, and executing commands.
… Why it matters: While many hoped for Opus 3.5, Anthropic’s Sonnet and Haiku upgrades pack a serious punch. Plus, with the new computer use embedded right into its foundation models, Anthropic just sent a warning shot to tons of automation startups—even if the capabilities aren’t earth-shattering… yet.
Also related/see:
What is Anthropic’s AI Computer Use? — from ai-supremacy.com by Michael Spencer Task automation, AI at the intersection of coding and AI agents take on new frenzied importance heading into 2025 for the commercialization of Generative AI.
New Claude, Who Dis? — from theneurondaily.com Anthropic just dropped two new Claude models…oh, and Claude can now use your computer.
What makes Act-One special? It can capture the soul of an actor’s performance using nothing but a simple video recording. No fancy motion capture equipment, no complex face rigging, no army of animators required. Just point a camera at someone acting, and watch as their exact expressions, micro-movements, and emotional nuances get transferred to an AI-generated character.
Think about what this means for creators: you could shoot an entire movie with multiple characters using just one actor and a basic camera setup. The same performance can drive characters with completely different proportions and looks, while maintaining the authentic emotional delivery of the original performance. We’re witnessing the democratization of animation tools that used to require millions in budget and years of specialized training.
Also related/see:
Introducing, Act-One. A new way to generate expressive character performances inside Gen-3 Alpha using a single driving video and character image. No motion capture or rigging required.
Google has signed a “world first” deal to buy energy from a fleet of mini nuclear reactors to generate the power needed for the rise in use of artificial intelligence.
The US tech corporation has ordered six or seven small nuclear reactors (SMRs) from California’s Kairos Power, with the first due to be completed by 2030 and the remainder by 2035.
After the extreme peak and summer slump of 2023, ChatGPT has been setting new traffic highs since May
ChatGPT has been topping its web traffic records for months now, with September 2024 traffic up 112% year-over-year (YoY) to 3.1 billion visits, according to Similarweb estimates. That’s a change from last year, when traffic to the site went through a boom-and-bust cycle.
Google has made a historic agreement to buy energy from a group of small nuclear reactors (SMRs) from Kairos Power in California. This is the first nuclear power deal specifically for AI data centers in the world.
Hey creators!
Made on YouTube 2024 is here and we’ve announced a lot of updates that aim to give everyone the opportunity to build engaging communities, drive sustainable businesses, and express creativity on our platform.
Below is a roundup with key info – feel free to upvote the announcements that you’re most excited about and subscribe to this post to get updates on these features! We’re looking forward to another year of innovating with our global community it’s a future full of opportunities, and it’s all Made on YouTube!
Today, we’re announcing new agentic capabilities that will accelerate these gains and bring AI-first business process to every organization.
First, the ability to create autonomous agents with Copilot Studio will be in public preview next month.
Second, we’re introducing ten new autonomous agents in Dynamics 365 to build capacity for every sales, service, finance and supply chain team.
10 Daily AI Use Cases for Business Leaders— from flexos.work by Daan van Rossum While AI is becoming more powerful by the day, business leaders still wonder why and where to apply today. I take you through 10 critical use cases where AI should take over your work or partner with you.
Emerging Multi-Modal AI Video Creation Platforms The rise of multi-modal AI platforms has revolutionized content creation, allowing users to research, write, and generate images in one app. Now, a new wave of platforms is extending these capabilities to video creation and editing.
Multi-modal video platforms combine various AI tools for tasks like writing, transcription, text-to-voice conversion, image-to-video generation, and lip-syncing. These platforms leverage open-source models like FLUX and LivePortrait, along with APIs from services such as ElevenLabs, Luma AI, and Gen-3.
How can judges handle #deepfakes under the Federal Rules of Evidence and Federal Rules of Civil Procedure?
Great to work on this interdisciplinary CS+Law project with computer scientists, lawyers, and judges!https://t.co/TXEVuA5de9@vssubrah
Maura R. Grossman@gcyzsl…
Great audience questions today when presenting with @Andrew_Perlman about the benefits and risks of judges and lawyers using AI for legal tasks. Andy and I agree that we are just scratching the surface of what can be done with AI systems.
Employers Say Students Need AI Skills. What If Students Don’t Want Them? — from insidehighered.com by Ashley Mowreader Colleges and universities are considering new ways to incorporate generative AI into teaching and learning, but not every student is on board with the tech yet. Experts weigh in on the necessity of AI in career preparation and higher education’s role in preparing students for jobs of the future.
Among the 5,025-plus survey respondents, around 2 percent (n=93), provided free responses to the question on AI policy and use in the classroom. Over half (55) of those responses were flat-out refusal to engage with AI. A few said they don’t know how to use AI or are not familiar with the tool, which impacts their ability to apply appropriate use to coursework.
But as generative AI becomes more ingrained into the workplace and higher education, a growing number of professors and industry experts believe this will be something all students need, in their classes and in their lives beyond academia.
From DSC: I used to teach a Foundations of Information Technology class. Some of the students didn’t want to be there as they began the class, as it was a required class for non-CS majors. But after seeing what various applications and technologies could do for them, a good portion of those same folks changed their minds. But not all. Some students (2% sounds about right) asserted that they would never use technologies in their futures. Good luck with that I thought to myself. There’s hardly a job out there that doesn’t use some sort of technology.
And I still think that today — if not more so. If students want good jobs, they will need to learn how to use AI-based tools and technologies. I’m not sure there’s much of a choice. And I don’t think there’s much of a choice for the rest of us either — whether we’re still working or not.
So in looking at the title of the article — “Employers Say Students Need AI Skills. What If Students Don’t Want Them?” — those of us who have spent any time working within the world of business already know the answer.
#Reinvent #Skills #StayingRelevant #Surviving #Workplace + several other categories/tags apply.
For those folks who have tried AI:
Skills: However, genAI may also be helpful in building skills to retain a job or secure a new one. People who had used genAI tools were more than twice as likely to think that these tools could help them learn new skills that may be useful at work or in locating a new job. Specifically, among those who had not used genAI tools, 23 percent believed that these tools might help them learn new skills, whereas 50 percent of those who had used the tools thought they might be helpful in acquiring useful skills (a highly statistically significant difference, after controlling for demographic traits).
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.
Top Software Engineering Newsletters in 2024 — from ai-supremacy.com by Michael Spencer Including a very select few ML, AI and product Newsletters into the mix for Software Engineers.
This is an article specifically for the software engineers and developers among you.
In the past year (2023-2024) professionals are finding more value in Newsletters than ever before (especially on Substack).
As working from home took off, the nature of mentorship and skill acquisition has also evolved and shifted. Newsletters with pragmatic advice on our careers it turns out, are super valuable. This article is a resource list. Are you a software developer, work with one or know someone who is or wants to be?
