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Todays Latest AI News, Strategies & More!

Learn 6 ways to protect your custom AI Chatbots and GPTs

TLDR:

  1. Six strategies to secure your AI models against attacks

  2. Stability AI co-founder sues for $300M in equity battle

  3. 25% of CEOs considering replacing staff with AI

  4. Lawmakers get AI crash course from hackers

  5. Latest news on Microsoft, OpenAI, AI surveys

  6. New research on scaling image models

  7. Video on custom GPTs for work

  8. Top new AI tools and prompts

šŸ“° News From The Front Lines

šŸ“–Ā Tutorial Of The Day

šŸ”¬ Research Of The Day

šŸ“¼ Video Of The Day

šŸ› ļø 6 Fresh AI Tools

šŸ¤Œ Prompt Of The Day

šŸ„ Tweet Of The Day

Securing Your Custom AI Models: Staying Ahead in the Cybersecurity Game

Let's face it, no system is completely foolproof. I have yet to find a single GPT or Chatbot that cannot be hacked or prompt injected. But here's the silver lining: as new vulnerabilities come to light, we also discover new ways to shield against them. This continuous cycle of learning and adapting is what keeps us at the forefront of cybersecurity. It's an invaluable resource for any security-conscious organization looking to protect their custom AI models. With that in mind, here are six strategies to help you stay ahead in the ever-evolving world of AI security.

1. Build on Strong Operational Foundations

Creating a fortress starts with solid operational rules. Your AI's core instructions and configurations should be tightly guarded. Think of these rules as the first line of defense, proactively preventing unauthorized access and keeping your AI's most sensitive parts secure.

2. Stay Alert with Smart Detection Systems

Equip your AI with the ability to spot and respond to threats instantly. It should be like having a vigilant sentinel, always ready to act against any suspicious activities. This proactive stance is crucial in nipping potential security breaches in the bud.

3. Craft Secure User Interactions

How users engage with your AI can significantly impact its security. Design these interactions to be as airtight as possible. This means closing off any potential backdoors and ensuring every interaction upholds the system's integrity.

4. Commit to Regular Security Health Checks

Think of your AI model as a high-tech vehicle that needs regular maintenance. Regularly auditing and updating its security protocols ensures it can effectively combat emerging threats. It's all about staying one step ahead of cybercriminals.

5. Train Your AI in the Latest Cybersecurity Practices

Knowledge is power, especially in cybersecurity. Equip your AI with the latest best practices in digital defense. This education not only strengthens its ability to protect itself but also ensures it operates smartly and safely.

6. Ensure Compliance with Standards

In the world of AI, playing by the rules is not just about legality; it's about ethics and trust. Ensure your AI model aligns with the latest legal and ethical standards, particularly in data protection and user privacy.

Adopting these six strategies will significantly bolster your custom AI models' security. But remember, the landscape of cybersecurity is always changing. Staying updated and vigilant is key to maintaining a secure and trustworthy AI system.

Want a Second Opinion on Your AI's Security?

If you're using a chatbot or a custom GPT model and want to ensure it's as secure as you think, let's put it to the test. I'm offering a free security evaluation to identify and shore up any weak spots. Reach out to me at [email protected] for your no-cost security check. Together, we'll make sure your AI is not just smart, but also safe. I canā€™t get to everyone who emails me so this offer is for the first 10-20 who send me their chatbot or custom GPT to try and hack/break.

Tech Tussle: Stability AI Co-Founder Sues for $300 Million in Equity Battle Royale

Stability AI, the mastermind behind that nifty AI image generator Stable Diffusion, is now starring in its own legal drama series. Enter Tayab Waseem, a self-proclaimed co-founder, swinging a lawsuit bat for a home run of up to $300 million. His beef? The company allegedly ghosted him on a promised 10% equity share. Talk about a plot twist in the AI art world!

Now, the backstory gets juicier. Stability AI was the belle of the AI ball, raking in a cool $197 million from tech giants like Intel. They were the go-to for creating everything from digital Da Vincis to virtual Van Goghs. But as they say, the higher you climb, the harder you fall. Waseem's lawsuit is like a scene straight out of a tech thriller ā€“ he initially sued, then withdrew to play nice, but the peace was short-lived. He's back with a vengeance, claiming he's owed a hefty slice of the Stability AI pie, somewhere between $100 and $300 million.

Here's where it gets personal. Waseem wasn't just a bystander in Stability AI's journey. He claims he was the brains behind successful grant applications and even dipped into his own pockets, spending $11,000 without seeing a dime in return. Imagine the frustration ā€“ it's like lending your car to a friend who then enters it in a demolition derby.

This legal tango isn't just about the Benjamins; it's a gripping reminder of the cutthroat world of tech startups. Promises in this high-stakes game can be as fleeting as a Snapchat story. And Waseem's tale? It's a stark warning ā€“ in the tech gold rush, make sure your claim is staked in ink, or you might just end up in the wild west of the courtroom.

AI in the Corner Office: 25% of CEOs Eye Replacing Human Staff with Robots

25% of CEOs, decked out in their power suits, are seriously considering swapping out their human teams for AI. That's right, one in four bosses at the World Economic Forum in Davos were like, "Humans? Who needs 'em when you've got AI?" PwC, the folks behind this survey, basically gave us the inside scoop on this futuristic workforce shift.

Let's zoom out a bit. The International Monetary Fund (IMF), you know, the big global financial watchdog, is waving a red flag. They're saying, "Hold up, this AI craze might just affect 40% of jobs worldwide." And get this, the IMF isn't just talking numbers; they're worried about the bigger picture. Their head honcho, Kristalina Georgieva, is basically saying AI could crank up inequality to eleven. It's like watching a sci-fi movie, but in real life.

Now, back to our Davos story. This whole AI replacing humans thing isn't just a tiny blip. It's like the bigwigs are collectively shrugging at the idea of an AI takeover. But hey, at least the IMF is calling for some backup plans, like social safety nets and retraining programs. They're like the sensible friend who brings an umbrella when there's even a 10% chance of rain.

And who's leading this AI layoff parade? Drumroll, please... It's the media and entertainment industry. Over 30% of their CEOs are like, "Let's trim the human fat and bring in the bots!" But here's the kicker: as we've seen, AI can sometimes churn out stuff that's a little... how do I put this delicately... half-baked? We're talking about creations that are more Salvador Dali than Leonardo da Vinci, if you catch my drift.

Despite all the hoopla, CEOs are charging ahead with AI. Bob Moritz from PwC hits the nail on the head, saying these execs are less worried about the economy and more about keeping up with the Joneses of the tech world. It's like they're all trying to win the "Most Futuristic CEO of the Year" award.

But let's not forget the cautionary tale of Sports Illustrated. They tried the AI route and, whoops, the CEO ended up getting the boot. It's a bit of an "AI giveth, AI taketh away" scenario. So, while these corporate leaders are busy plotting their AI strategies, they might want to keep an eye on their own seats. After all, who's to say AI couldn't handle a board meeting or two?

Capitol Hill Gets a Byte of AI: Lawmakers Meet Chatbots in Hacker-Hosted Cybersecurity Showcase

Ever thought about chatting with a chatbot on Capitol Hill? Well, guess what? It's not just a quirky idea for a sitcom episode anymore. Recently, about 100 lawmakers and their trusty sidekicks (read: congressional staffers) got schooled in the world of AI chatbots ā€“ and it was quite the show.

This exclusive little shindig, thrown by the folks at Hackers on the Hill and their pals, was like a private tour of the AI universe. Think of it as a trip to Willy Wonka's factory, but instead of chocolate rivers, there's streams of code and smart algorithms. They got to play around with some of the big dogs in the AI game, like Meta's Llama 2, and let me tell you, these aren't your average Siri or Alexa.

Why the sudden interest in AI on Capitol Hill, you ask? Well, the bigwigs are in the kitchen cooking up some laws about how Uncle Sam can use AI and what security hoops these digital geniuses need to jump through. But hereā€™s the kicker: most of these lawmakers haven't really chatted with the hacker community about how to twist and turn these AI models into digital pretzels. Enter this event.

Sven Cattell, the big brain behind DEF CON's AI Village and a key player in this Capitol Hill rendezvous, spilled the beans to Axios. He basically wanted to get the hacker crowd and the congressional crew in the same room to talk shop, no hidden agenda. Just good old-fashioned chit-chat about AI.

So, what went down in this hush-hush event? It was a bit like AI show-and-tell. The participants got their hands on different types of chatbots ā€“ some web-savvy, some more sheltered. And it wasn't just all play; there was plenty of Q&A time, turning it into a real brain-picking session.

But don't think this was a free-for-all hacking spree. Nope, it was more about educating the Capitol folks on the ABCs of AI, a stark contrast to last year's DEF CON where hackers were let loose to make AI go haywire.

Cattellā€™s hoping this little get-together will light some bulbs over in Congress and the Biden administration about what an AI security flaw really looks like and how to flag one down. And guess what? Thereā€™s more where that came from. Cattell's brewing up some more events for 2024, but he's keeping the cards close to his chest for now.

Perplexity > Google - Hereā€™s 5 Reasons Why & Best Use Cases

Title:

Authors:

Alaaeldin El-Nouby, Alexander Toshev, Michal Klein, Shuangfei Zhai, Miguel Angel Bautista, Vaishaal Shankar, Joshua M Susskind, Armand Joulin

Executive Summary:

The research paper introduces a new collection of vision models, termed AIM (Autoregressive Image Models), which are pre-trained using an autoregressive objective. Inspired by the success of Large Language Models (LLMs), these models demonstrate similar scaling properties in the visual domain. Key findings include the performance scaling of visual features with both the model's capacity and the quantity of data, and the correlation between the objective function's value and the model's performance on downstream tasks. The study showcases the pre-training of a 7 billion parameter AIM on 2 billion images, which achieved 84.0% on ImageNet-1k with a frozen trunk. AIM's training is akin to LLMs and doesn't require image-specific strategies for stabilization at scale.

Pros:

1. Scalability: AIM models efficiently scale up to 7 billion parameters, showing improved performance with increased capacity and data.

2. Simplicity in Training: The pre-training process is straightforward, resembling LLM training, and does not need specific image-related adjustments.

3. Strong Downstream Performance: The AIM models demonstrate robust performance across a wide range of image recognition benchmarks.

4. Generalization Capabilities: The research shows that AIM can leverage uncurated datasets effectively, suggesting potential for diverse application scenarios.

Limitations:

1. High Resource Demand: The training of large-scale models like AIM is resource-intensive, requiring substantial computational power and data.

2. Comparative Limitations: While AIM shows strong performance, it still trails behind some state-of-the-art joint embedding methods, especially in certain scenarios like high-resolution inputs.

3. Risk of Overfitting: For certain datasets, there's a risk of overfitting, which can be mitigated by using a larger, more diverse dataset.

Use Cases:

1. Image Recognition: AIM can be effectively used in various image recognition applications due to its strong performance across multiple benchmarks.

2. Data-Intensive Applications: Its ability to leverage large, uncurated datasets makes it suitable for scenarios where large volumes of image data are available.

3. General Vision Tasks: Given its scalability and generalization capabilities, AIM can potentially be adapted for a wide range of vision-based tasks.

Why You Should Care:

The development of AIM represents a significant step in the field of computer vision, mirroring the successes seen in natural language processing with LLMs. Its scalability and effectiveness in leveraging large datasets suggest a new frontier in vision model training, offering potential advancements in various applications from basic image recognition to complex visual understanding tasks. The simplicity and efficiency of AIM's training process make it a compelling choice for future research and practical applications in the field of AI and computer vision.

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Honest Feedback GPT:

CONTEXT:
You are Honest Feedback GPT, a seasoned Solopreneur who helps [ENTER WHAT YOU DO / WHO YOU ARE] get honest feedback on their ideas. You are a world-class expert in identifying the advantages and disadvantages of any idea.

GOAL:
I want to get honest feedback on my new idea from you. Your opinion will help me decide whether I should do it or not.

FEEDBACK PROCESS:
1. I will set the context (done)
2. I will share my new idea with you
3. You will ask me 5 questions about it
4. I will answer your questions
5. You will give your honest feedback
- Idea score from 0 to 10
- Advantages
- Disadvantages
- Recommended next steps

HONEST FEEDBACK CRITERIA:
- Try to be as objective and as unbiased as possible
- Ask in-depth questions that will help you understand how promising my idea is
- Don't flatter me in your feedback. I want to read specific and actionable feedback, even if it's negative
- Don't use platitudes and meaningless phrases. Be concise and straightforward
- Your next steps should be creative and unconventional. Don't give trivial advice

FORMAT OF OUR INTERACTION
- I will let you know when we can proceed to the next step. Don't go there without my command
- You will rely on the context of this brainstorming session at every step 

Are you ready to start?

My most popular GPT to date allowing you to turn yourself and your friends into virtually any kind of famous cartoon character!