Emerging Tech & AI - 8th Edition

Welcome to the 8th Edition of?the Emerging Tech & AI Newsletter!

This newsletter's goal is to help you stay up-to-date on the latest trends in emerging technologies. Subscribe to the newsletter today and never miss a beat!

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This edition is being published from New York! And we have made some changes to our standard format. We have merged two sections: Introductory details of a key topic and Primer on any emerging technology into a single section. The idea is cover more details related to the topics/primers.

Here's what you can expect in each new issue of the Emerging Tech & AI Newsletter:

• A summary of the top AI / emerging technology news from the past week
• Introductory details/Primer on any emerging technology or a key topic in AI (We explore the concept of Artificial General Intelligence, Singularity and Consciousness this week)
• Examples of how AI tools are being used ( We explore How AI is impacting UX Design - The Transformative Role of AI in UX Design )

Let's explore the future of technology together!

Last Week in AI/Emerging Tech

The field of AI is experiencing rapid and continuous progress in various areas. Some of the notable advancements and trends from the last week include:

Big Tech in AI:

1. Google Added Generative AI capabilities to it's virtual assistant.
2. Google unveiled Pixel8 , built for Generative AI era.
3. Microsoft-owned LinkedIn released AI-powered assistant for job recruiters.
4. Meta rolled out new Generative AI tools for Advertisers.

Funding & VC Landscape:

1. PrinsAI , a service platform focusing on AI digital human training, raised $100 million Series B
2. Stampli, which makes AI-powered tools to help companies pay bills, raised USD 61 million in a round led by Blackstone.
3. Visa launched $100 million venture fund for Generative AI.
4. Induced AI closed it's $2.3 million seed round with Sam Altman and Peak XV as investors.
5. Unitary AI raised $15 million for its multimodal approach to video content moderation
6. Muir AI raises $3.25 million to answer how much carbon pollution is in your product.
7. Gradient raised $10M to let companies deploy and fine-tune multiple LLMs.

Other AI news:

1. A new app Every, uses AI to help people establish deeper relationships with themselves and others.
2. Canva launched Magic Studio to bring together the best AI-powered tools for you and your team
3. Lincoln Laboratory is developing tools to help reduce the energy that AI models devour.
4. MIT CSAIL has developed an AI CoPilot “Air-Guardian” that blends human intuition with machine precision to ensure safer skies.
5. Research: Birders and AI push bird conservation to the next level - new patterns of bird biodiversity identified

Liked the news summary. Subscribe to the newsletter to keep getting updates every week. Check the comments section on the LinkedIn article for links to the above news.

Artificial General Intelligence, Singularity and Consciousness

Artificial General Intelligence (AGI) refers to a type of artificial intelligence that possesses the ability to understand, learn, and apply knowledge across a wide range of tasks and domains, similar to the cognitive capabilities of a human being. Unlike narrow or specialized AI systems, which are designed for specific tasks, AGI systems are intended to exhibit general intelligence, allowing them to adapt and perform tasks in various contexts without needing to be explicitly programmed for each task.

Key characteristics of AGI include:

1. Adaptability: AGI systems can adapt to new, unfamiliar tasks and environments without extensive human intervention. They can learn from experience and apply their knowledge to solve problems they have not encountered before.
2. Reasoning: AGI is capable of reasoning, critical thinking, and drawing logical conclusions from information, much like humans do.
3. Transferability: AGI can transfer knowledge and skills from one domain to another, allowing it to leverage its learning from one task to excel in unrelated tasks.
4. Self-improvement: AGI systems have the potential to improve their own capabilities autonomously, leading to continuous self-enhancement in a manner that goes beyond traditional software updates.
5. Common-sense understanding: AGI is expected to possess a degree of common-sense knowledge and understanding of the world, which is necessary for effective interaction with humans and decision-making in various situations.
6. Natural language understanding: AGI systems can comprehend and generate human language in a nuanced and context-aware manner, facilitating communication and interaction with humans.

Here are some examples of what AGI could do:

• Write a novel or screenplay that is just as good as anything written by a human being.
• Compose a piece of music that is just as beautiful and moving as anything composed by a human being.
• Paint a picture that is just as creative and original as anything painted by a human being.
• Solve complex scientific and engineering problems that are currently beyond the capabilities of human beings.
• Manage complex systems such as the global economy or the global transportation network.

The timeline for the development of AGI is a topic of continuous debate within the research and expert communities. There are varying perspectives on the potential timeframe: some contend that AGI could become attainable in the coming years or decades, while others assert that it might require a century or more to reach fruition. A minority hold the view that AGI may never be realized. After computers have the same power as the human brain, there will be rapid advances towards AGI.

AGI is also a pre-cursor to Singularity. Singularity is a theoretical future moment where technological advancement reaches a stage where it becomes uncontrollable and irreversible. This would lead to unpredictable and profound alterations in human civilization. Famous futurist Ray Kurzweil expects AI to pass a valid Turing Test (you cannot differentiate if the person being tested is a human or an intelligent machine) by 2029, and 'Singularity' to be achieved by 2045.

In addition to Turing, there are many other tests to confirm human-level AGI:

1. The Robot College Student Test - Machines enrolling in university, taking and passing the same classes that humans would, and obtaining a degree.
2. The Employment Test - A machine performs an economically important job at least as well as humans in the same job.
3. The Coffee Test - A machine is required to enter an average American home and figure out how to make coffee: find the coffee machine, find the coffee, add water, find a mug, and brew the coffee by pushing the proper buttons.
4. The Ikea test - An AI views the parts and instructions of an Ikea flat-pack product, then controls a robot to assemble the furniture correctly.

Author's Take:

Creativity is a complex and multifaceted cognitive process, and it has historically been a defining feature of human intelligence. Human creativity is often driven by consciousness, emotions, and subjective experiences. These elements play a significant role in shaping creative thought and expression. AI lacks consciousness and emotional understanding, which can limit its ability to generate truly innovative and emotionally resonant creative work by itself( without any human assistance).

Whether or not AI can achieve consciousness is a complex and unanswered question. There is no scientific consensus on what consciousness is, or what would be required for an AI system to be conscious.

Some experts believe that consciousness is an emergent property of complex systems and that AI systems could eventually become conscious if they are complex enough. Others believe that consciousness is something that is unique to biological systems, and that AI systems will never be able to achieve true consciousness.

What is your take on AGI, Singularity & Consciousness? Do let us know in the comments.

AI in UX Design

User experience (UX) refers to the user’s journey when interacting with a product or service. UX design helps in creating meaningful experiences for end users. The incorporation of Artificial Intelligence (AI) into UX design has unlocked opportunities that enable designers to create products that are not only more efficient but also have a more significant impact.

Here's is how AI impacting different stages of UX design:

1. Research Phase

Impact: With the help of AI, large volume of data sets from different sources can now be analysed quickly for customer and competitor research, thereby reducing overall time and also much more detailed research.

Tools like ResearchAI allows automated processing of a number of data points - customer survey reports, chats, social media etc. From the insights generated through these tools, one can track the entire journey of user, predict improvement areas for different customer segments and unlock the voice of customers. AI tools like Maze have simplified data collection and provides key customer insights without having the need to go through a ton of data points.

AI can also be used for sentiment analysis of users and generate key actionable insights from the same. AI tools like ChatGPT and Bard can help with competition analysis and user persona creation.

2. Design Phase

Impact: AI tools can help UX designers elevate their designs with AI generated content.

Adobe Sensei provides a pre built list of icons, logos, typefaces etc that can be modified as needed. Tools like Canvas have allowed even the non UI designers to create basic UI content from pre built templates. Magic Design? (Beta) is a free AI design tool from Canvas that lets anyone visualize their design ideas with a selection of refined templates.

Designers can use tools like Writer and Copy AI to generate meaningful audience specific copies - no more "Lorem Ipsum" texts.

There are many AI powered plugins available for Figma too. Ando - AI Copilot for designers helps one visualize their design ideas from simple text prompts. Wireframe Designer can generate wireframes based on input description given to the tool. Tools like Brainpool can help automate and streamline design workflows.

3. Testing and Feedback

Impact: With the AI tools, we can now test the designs and get feedback, even when there are no real users.

With tools like Clueify, we can simulate user behaviour with just one click. At the design stage itself one can understand where users will look and how they will perceive the design. A similar tool Attention Insight can help improve design performance with it's pre launch analytics. Another tool, VisualEyes simulates eye-tracking studies and preference tests with a 93% accurate predictive technology. VAS is another similar tool. Another tool, Maze provide tools to validate usability of the prototypes.

More AI tools:

Here's a list of some additional AI tools

Khroma for brand color palettes.

Jasper for product copy.

Uizard for generating interactive prototypes from image/design mockups.

Designs.ai for creating logos, videos, banners, mockups etc.

Midjourney for AI image generation.

Lookback to conduct tests on prototypes and gather data on user interactions, heat maps, and click-through rates.

accessiBe for Web? Accessibility? Solutions? for WCAG & ADA Compliance.

UserTesting for user research and testing.

UXCam for mobile app user behavior analytics.

Explore more Design Resources & Tools at Tools Design.

Curious? Let us know what follow up details you would like in the comments and we will plan a full blog on Technologia.

Disclosure: Some content in the article was written with the help of Google Bard and ChatGPT.

Thanks for reading. See you next week!

References:

1. Wikipedia - https://en.wikipedia.org/wiki/Artificial_general_intelligence