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The latest trends in AI and generative technology
A photo of a modern music studio filled with traditional instruments like guitars, pianos, and drums.

Table of Contents


Time Magazine's AI top list

In November, Time Magazine listed 12 AI products as the year's best inventions. These include Adobe's AI tools Photoshop Camera and generative image creation Phil. Startups with new AI tools like Runway Gen 2 and Anthropic with Claude AI are also on the list.

The fact that so many AI solutions are highlighted shows how central AI has become for innovation and technical development. At the same time, established tech companies have started to integrate AI more deeply into their products.


AI music creation tools

AI music is a rapidly growing field. One of the leading AI models is Sovit SVC, which is used to create fully AI-generated songs.

Blind listening tests show that it is difficult to determine whether the music came from AI or human artists. Sovit SVC has been used to create songs in the style of rappers like Drake and Kanye West.

Although AI music is still limited, it can provide new tools and inspiration for human musicians and songwriters.


Faster AI generated images

Mid Journey recently released a beta version of its website with AI-generated images. The focus has been on making the search function faster and being able to filter images with different tags.

The user experience is much better when you can quickly find the desired images based on text descriptions. It is important that AI services are optimized for usability, not just technical performance.

Mid Journey appears to be at the forefront when it comes to user-friendly AI image tools online.

An illustration showing two side-by-side monitors.



AI assisted image editing

The image provider Shutterstock recently integrated AI-based editing features into its service. These include a "magic wand" that identifies and modifies specific objects in images.

Other news is background removal and generation of new image sections with AI. The goal is to make advanced image editing accessible to more users, without expert knowledge.

AI-assisted editing can save time and make it easier to create visually appealing images. At the same time, it raises questions about copyright and ownership.


AI for product ads

Amazon launched an AI tool to enhance product ads with generated images. The images are created based on text descriptions and existing product photos.

The tool is intended to help sellers visualize products in a more appealing way. For example, adding backgrounds or changing angles.

While image quality is still limited, AI-generated ads could revolutionize e-commerce in the long run. At the same time, ethical aspects must be considered when AI is used commercially.


Google's image review tools

Google presented new tools to review the origin and reliability of images using AI. The idea is to provide users with more context for images they encounter online.

One tool is "Image Fact Check" which compares images against known originals to identify manipulations. Another is "What's in this image" which textually describes objects and locations in images.

Google's initiative demonstrates the importance of countering fake news and disinformation online. AI can create both new opportunities and challenges in this area.


Disrupting AI models' training data

An interesting experiment with disrupting AI models' training data was recently presented. The Nightshade tool manipulates training images to get models to generate chaotic results.

By adding subtle glitch effects or twisting the images a few degrees, the AI models' generated output can be severely distorted.

The experiment shows how sensitive generative AI models are to their training data. Small changes in the learning material have major effects on the result.


Investments in AI safety

In recent months, several tech companies have announced investments in AI safety and ethics. OpenAI, Anthropic, Google and Microsoft are allocating significant funds for research.

The efforts range from preventing harmful use of AI to ensuring models do not reproduce discriminatory patterns from training data.

While the intentions are good, much work remains to be done to solve AI safety in practice. Progress can be made through open research and collaboration.


Bug bounties for generative AI

In line with the investments in AI safety, Google and Microsoft have introduced bug bounty programs for their generative models. Developers are encouraged to report vulnerabilities or risks related to the models.

The programs offer rewards of up to several thousand dollars for more serious bugs. The idea is to engage a broader group in reviewing the AI systems.

Treating AI models like regular software with continuous security testing is a step in the right direction.


AI voice imitation

YouTube is reportedly working on a tool where AI can imitate famous artists' voices. The tool is intended to insert celebrity voices into videos, similar to deepfake technology.

Although voice imitation with AI is already possible, an official YouTube tool could significantly increase the spread.

However, imitating real people raises many ethical question marks. Clear guidelines and consent are needed to avoid abuse.


AI-created app prototypes

Google is considering introducing AI-generated app prototypes in its Gemini developer platform. The idea is to quickly create schematic "stubs" of app ideas.

In the long run, Google's new Maker Suite tools could also offer more advanced AI-assisted app development.

Automatically creating app prototypes with AI could lower the barriers to testing new ideas and iterating app design. But challenges with usability and scalability remain to be solved.


Robots with AI support

The robotics company Boston Dynamics recently demonstrated an AI integration in one of their robots. ChatGPT was used to generate voice-guided tours.

This shows the growing trend of combining AI and robotics. Through language understanding and generation, robots can interact more naturally with humans.

At the same time, it creates new risks when advanced AI systems are linked to robots' physical abilities. Safety and ethics must be prioritized.


Self-driving cars

In some US cities, Uber now offers rides in self-driving cars from Waymo. Waymo has test driven over 20 million miles with its autonomous vehicles.

Self-driving cars are a clear example of the application of AI in real products. Although development remains before it becomes mainstream, self-driving technology is moving forward quickly.

The benefit is increased safety and efficiency in transportation. Challenges exist around ethics, jobs, and infrastructure. Careful analysis is required before widespread launch.


Future AI development

In a recent interview, Bill Gates expressed skepticism about whether AI will continue to develop at the same rapid pace as before.

He believes there may not be as dramatic improvements between GPT-3 and GPT-4 as between GPT-2 and GPT-3.

Gates has a point in that the pace may slow down somewhat as AI becomes more advanced. But at the same time, he probably underestimates the long-term possibilities in AI and the power of exponential technological development.


Exaggerated AI concerns?

Meta's AI chief Yan LeCun claims that fears of AI threatening humanity are greatly exaggerated. He argues that current AI is not even close to human intelligence.

Certainly one should not draw hasty conclusions about the risks of AI. But LeCun's dismissal also fails to capture the full problem picture with more proximate challenges around bias, transparency and ethics.

To balance AI development responsibly requires both optimistic innovation and critical analysis. The best ideas often arise at the intersection.


Concluding reflection

Recent AI advances and product launches testify to a rapidly changing industry. Exciting opportunities are opening up while new challenges arise.

In upcoming articles and videos, we delve deeper into both the optimism and concerns surrounding AI. With a nuanced view, we can shape a responsible future.

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