🔥 Weekly AI news: Did you miss it?!

👨‍🚀 The most important AI updates at a glance

AI-HOI, AInauts!

Maybe you didn't catch all the news, tools, and hacks about AI last week, or maybe you've only recently joined us. Either way, here's our recap with all the headlines from the newsletter - just one click away!

Click the links to jump right to the article - or read our picks below.

• 📚 How to create a book in one minute ...

• 👀 𝕏 with Grok-2: Uncensored pictures and a loose mouth

• 🎭 How to generate ultra-realistic images (and videos)!

• 📰 AI news quickie: The HAI highlights from the industry

• 🤳 Deep Dive: Train your own image AI (e.g. of yourself)

• 🤯 Use several trained image AIs (LoRAs) at the same time

→ Selection of the top posts of the last week ←

📚 How to create a book in one minute ...

We have published many books by real authors on Amazon. And of course, since the advent of AI, we've been experimenting with what's possible (and what's not).

First we racked our brains on Google Sheets-based tools, endless ChatGPT conversations and specialized GPTs, and then we tried to get Gemini's massive context window to produce a long output. But it was never really usable ...

Sudowrite on the other hand was very good, but also involved a lot of manual effort. But now we’ve come across a new option that we would like to introduce to you today.

Infinite Bookshelf - fresh books in seconds

Developed on the basis of Meta's Llama3 models and the powerful Groq hardware, this app lets you create your book directly in the browser with a single prompt - faster than you can say "Simsalabim, write my book!".

1. Create an account with Groq (not to be confused with Grok, see below!) and get a free API key.

2. Open the app here and fill in the fields - the advanced version has even more parameters (Github from the creator Benjamin Klieger 🙏).

3. Simply enter a topic, click on "Generate" at the bottom - and the app generates complete chapters that logically build on each other

4. The app is particularly interesting for factual content, but fiction will also be better supported in the future.

5. After the generation, you can export the result as a text file or styled PDF.

6. Soon it will also be possible to save books directly to Google Drive and use notes as the basis for new projects.

And that's just the beginning, because new approaches are already on the horizon!

P.S.: The result is by no means ready for publication - but we think it's great for getting a comprehensive overview of any topic.

👀 𝕏 with Grok-2: Uncensored pictures and a loose mouth

You can think what you like about Elon (our index has been on the decline recently) ... but the richest man in the world is not only setting the pace with Tesla, SpaceX and Neuralink, he has now added a really solid AI to his X platform with Grok-2 from xAI.

The latest chatbot has a cheeky personality (we like it!) and can do more than just chat: it also generates controversial images of personalities, brands, etc., with virtually no filters ...

Risks and side effects: Images without filters and censorship

Images are therefore the most hotly debated new function of Grok-2. Almost every prompt is accepted, even controversial ones.

It is not even Grok's own model under the hood, but the new FLUX.1 model from Black Forest Labs, which is known for its photorealistic results (our article here). Elon has also announced that his company is already working on its own image AI.

This is a double-edged sword: on the one hand, you can unleash your creativity and create customized, (un)realistic images in a matter of seconds. On the other hand, such images lead to ... chaos, false reports, propaganda, slander, ...

Flashback: Remember the picture of the Pentagon explosion that caused a short-lived dip in the stock market? That will happen again, no half-hearted policy will prevent this...

And how good is the Grok-2 language model?

The predecessor Grok-1 was a big promise that disappointed in reality and couldn’t hold up in comparison with others. Even the open sourcing of the model could not hide this fact.

But Grok-2 is fun - and since the bot also has access to current information on X, it could be used in a variety of ways.

The latest Grok 2 model recently entered the LMSYS chatbot gladiator arena under the name "sus-column-r". There, it took one of the top spots on the podium, on par with OpenAI and Anthropic. Many even thought it might be a new ChatGPT model.

In addition to its big brother, there is also Grok-2 mini. This version was the first to be released on X. Both models will be available to companies via API in the coming weeks, and Grok-3 is due to be released this year.

Some data from European users is excluded from training - if you want to be on the safe side, you can actively switch this off.

What’s exciting in this context is that the field of language models is changing rapidly, and the best models on LMSYS have an ever-shorter half-life.

Our take: Promising, with potential for conflict

This time, Elon has produced more than just hot air with Grok-2. We got ourselves a premium account and have been playing around with it.

Grok-2 is not only smart and fun, but also up-to-date thanks to real-time information from X. Sure, the usual suspects like OpenAI and Anthropic aren't sleeping either. But with the pace that xAI is setting, it could get exciting. This thing has real potential.

Will the relatively uncensored images bring the regulatory authorities onto the scene? Certainly. But if AI-generated content is influencing public opinion and democracy, a broader discussion about it is definitely welcome.

Alright, if you want to check out Grok-2 for yourself, go to X and get a premium account for $8/month!

🤳 Deep Dive: Train your own image AI

For a few weeks now, the internet has been full of hype about the new Image AI FLUX, made in Germany. We have already written about it several times.

FLUX makes everything so much easier. And provides incredibly good quality.

In this tutorial, we show you an example which was previously only feasible for techies. But now, it can be done by anyone:

We train our own image AI that always creates images of the same person - for less than 5 dollars, without subscription tools!

Why is this useful?

Such trained models are called LoRAs. And if you're wondering why the hell this is exciting, here are a few reasons:

1) You always want to create images with the same person

This is ideal, for example, if you want to run an AI influencer account. Or you want to create images of yourself in places or situations you've never been.

2) You want to create images in a certain style that should always look the same

It is also super practical if you want to create coherent comics or if you need characters in the same style.

You can use LoRAs to make sure your images stay consistent with the person or style you want.

You may be familiar with websites like HeadshotPro and PhotoAI. Their founders earn millions and basically use the very same technology.

Step 1: You need the following tools

To train your own LoRA based on FLUX, you essentially need two platforms. Simply create free accounts:

• Replicate

• Hugging Face

(There is also another popular platform called Fal, but we picked Replicate for this example).

Step 2: Collect 12 images of your person or the desired style

In our specific use case, we create a LoRA for our AInauten influencer. May we introduce: AIlexa

If you want to create a LoRA of yourself, simply put together at least 12 photos of yourself.

In the next step, name the 12 pictures in the format: a_photo_of_PLACEHOLDER

In our case, all images are named: a_photo_of_Allexa

This is what our folder looks like. As you can see, it is a broad selection of images.

The naming is important, however, because your LoRA will understand this later when you write in the prompt: "Create a picture of AIlexa..."

The last step in the preparation is to create a ZIP-file of all your images.

Step 3: Set up Hugging Face model and token

We will now use Hugging Face to access the image models. To do this, please do the following:

1) Create an access token

To do this, go to "Settings" in your account and then to "Access Tokens".

Give your token a name and the rights as shown in the picture above. There are probably too many boxes checked, but it works. 😉

Save the token - we'll need it in a minute for Replicate.

2) Create a model repository

The next step is to create a folder for our model. Go to your profile and click on "New Model".

Here you give your model a descriptive name - in our case, for example, ailexa-lora. Set the model to Public here, otherwise Replicate will not work later on.

Step 4: Train your LoRA

Now it's time to train with Replicate.

Click here and open the AI Training Toolkit. Click on the "Train" tab.

The training is not entirely free. We use an Nvidia A100 chip from Replicate, and of course that costs something.

$0.0014 per second to be precise. This means that a trained model costs you between 2 and 5 euros.

Quite reasonable, we think.

Now it's time to fill in the training screen. This is also simple, we leave most of the values set to default. Here in detail:

If you want to use your model later via Replicate, select the Creating New Model entry under destination.

Under images, upload your ZIP-file with images.

In the field hf_token, enter your Hugging Face Token, which we have previously created.

For the repo_id, you enter the path of your model, which we have previously created in Hugging Face.

It always has the following format: yourUserName/yourModelName

You can leave all other values in the default state for now.

And that's it! Let’s start the training.

You’ll see in Replicate once the training is complete. In our Allexa case, this took 38 minutes and the cost was $3 USD.

Step 5: Use your LoRA

The easiest way to use your LoRA now is again via a model on Replicate.

Step 1: Get your LoRA path from Hugging Face

To do this, simply click on the model you have previously created and copy the path.

Step 2: Click here and open the LoRA Explorer on Replicate

Now create a prompt using the name you defined for your LoRA. In our example, we want a picture of AIlexa:

You can leave the remaining values as default. You only need to add your LoRA with the hugging face path from step 1 in hf_lora

And the result of the prompt from above?

Here is our influencer AIlexa once again as a speaker at an innovation conference:

After the work was done, AIlexa first went out and about to Paris:

Alright, that’s it! We hope you liked it and it makes you want to try it out.

It really is incredible what we can now do with AI without any technical skills and for less than $5 dollars.

As always, please get in touch if you have any questions.

🤯 Use multiple trained image AIs (LoRAs) together

And for those who want even more: You have the option of using several specially trained LoRAs (or LoRAs provided by others) at once.

To do this, use this replicate model.

It allows you to add up to 20 different LoRAs, e.g. from Hugging Face and Co.

Simply add each one individually, just as we have already added your own above. The cool thing here is that you can then connect your personal LoRA with a style LoRA, for example.

Here is a "knitted" person:

Your AInauts, Fabian & Reto

Follow us on Twitter & LinkedIn!

Your feedback is essential for us. We read EVERY comment and feedback, just respond to this email. Tell us what was (not) good and what is interesting for YOU.