Future Forward - 107th Edition - Last Week in AI - AI & Cognitive Science

Welcome to the 107th Edition of Future Forward - the Emerging Tech & AI Newsletter!

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Each edition covers top AI news from last week and an AI-related topic - Primers/Tutorials/ How AI is being used.

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

• A summary of the top AI news from the past week.
• Bridging Minds and Machines.

AI News from Last Week

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

Big Tech in AI:

1. Microsoft announced MAI-Voice-1 and MAI-1-preview, it's first homegrown models.
2. Microsoft Copilot is now available on TVs too.
3. Google is rolling out new features to is Vids AI video editing platform.
4. Google's nano banana(Gemini Flash 2.5 Image) is a hit.
5. Google added AI upgrades to its Google Translate platform.
6. Microsoft released VibeVoice, a new open-source text-to-speech model.
7. Nvidia's Jetson Thor robotics computer is GA.
8. NotebookLM gets multilingual upgrade.
9. Meta announced partnership with Midjourney to integrate the startup’s ‘aesthetic technology.
10. Meta FAIR researchers released DeepConf.

Funding & VC Landscape:

1. BlueJay raised $4M in funding.
2. Creem got €1.8M.
3. Holiwise bagged €1.45M.
4. OpenLight raised $34M.
5. Attio gets $52M for AI native CRM.
6. Instalily raised $25M.
7. Aurasell raised $30M.
8. Lovable surged to $4B valuation.
9. Romanus raised €1.5M.
10. CrowdStrike to acquire Spanish startup Onum for $290M.
11. NZ awards $2.7M funding for AI projects.

Other AI news:

1. Augment code launched Auggie CLI.
2. Open AI's Realtime API is out of beta.
3. Cohere launched Command AI Translate.
4. xAI launched Grok Code Fast 1, a new advanced coding model.
5. OpenAI launched new features for Codex software development tool.
6. Tencent opensourced HunyuanVideo-Foley model.
7. Nous Research introduced Hermes 4 model.
8. Anthropic launched “Claude for Chrome” extension.
9. AI2 introduced Asta.
10. xAI open sourced Grok 2.5 model.
11. Baidu launched MuseStreamer 2.0 model.

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Bridging Minds and Machines: The Future of AI is Human-Inspired

Have you ever wondered what the secret ingredient is to creating truly intelligent machines? Is it more data? Faster processors? Or is it something more... human?

A recent research paper, "Bridging Minds and Machines: Toward an Integration of AI and Cognitive Science," argues for the latter. The authors make a compelling case that the future of artificial intelligence lies in a deeper, more meaningful collaboration with cognitive science. This isn't just about making AI "smarter" in a narrow, task-oriented way; it's about building machines that can reason, learn, and interact with the world in a way that is fundamentally more human.

Bridging Minds and Machines: The Future of AI is Human-Inspired

Have you ever wondered what the secret ingredient is to creating truly intelligent machines? Is it more data? Faster processors? Or is it something more... human?

A recent research paper, "Bridging Minds and Machines: Toward an Integration of AI and Cognitive Science," argues for the latter. The authors make a compelling case that the future of artificial intelligence lies in a deeper, more meaningful collaboration with cognitive science. This isn't just about making AI "smarter" in a narrow, task-oriented way; it's about building machines that can reason, learn, and interact with the world in a way that is fundamentally more human.

The Symbiotic Relationship Between AI and Cognitive Science

AI has focused on building intelligent systems, while cognitive science has focused on understanding the mechanisms of the human mind. However, the authors of this paper argue that these two fields are not just complementary; they are symbiotic. AI can provide powerful tools for modeling and testing theories of human cognition, allowing us to simulate complex mental processes and gain a deeper understanding of how our own minds work. In return, cognitive science can offer a wealth of knowledge about the principles of natural intelligence, providing a blueprint for building more robust, flexible, and human-like AI.

Key Areas of Integration: A Multidisciplinary Approach

The paper highlights several key areas where the integration of AI and cognitive science can yield groundbreaking results:

• Philosophy : At its core, the quest for AI is a philosophical one. What is consciousness? What does it mean to be intelligent? By engaging with these profound questions, we can develop a more nuanced understanding of what we are trying to achieve with AI and avoid the pitfalls of creating systems that are intelligent in a purely superficial way.
• Psychology : How do humans learn, remember, and reason? Psychology offers a rich tapestry of theories and models that can be used to inform the design of AI systems. For example, by incorporating psychological models of emotion, such as appraisal theory, we can create AI that is not just "smart" but also emotionally intelligent, capable of understanding and responding to human emotions in a more empathetic way.
• Neuroscience : The human brain is the most complex and powerful computational device known to exist. By studying its structure and function, we can gain invaluable insights into how to build more efficient and powerful neural networks. Brain-inspired AI is not just a futuristic dream; it's an active area of research that is already yielding promising results.
• Linguistics : Language is the cornerstone of human intelligence. To create AI that can truly understand and communicate with us, we need to go beyond statistical pattern matching and embrace the rich and complex structures of human language. By incorporating insights from linguistics, we can build natural language processing (NLP) models that are not just fluent but also truly meaningful.
• Culture : Intelligence is not a monolithic entity; it is shaped by the cultural context in which it develops. To create AI that can interact with people from all walks of life, we need to build systems that are culturally aware and adaptable. This means going beyond simply translating languages and instead understanding the subtle nuances of cultural norms, values, and communication styles.

The Road Ahead: Towards a More Human-Centered AI

The authors of "Bridging Minds and Machines" envision a future where AI and cognitive science are no longer separate disciplines but a unified field of study. This integration, they argue, will be the key to unlocking the full potential of artificial intelligence and creating machines that can not only solve complex problems but also enrich our lives in a meaningful way.

The road to artificial general intelligence (AGI) is long and challenging, but by bridging the gap between minds and machines, we can take a significant step forward. The future of AI is not just about building smarter machines; it's about building machines that are more human.

What are your thoughts on the integration of AI and cognitive science? Share your insights in the comments below! 👇

#AI #CognitiveScience #ArtificialIntelligence #MachineLearning #DeepLearning #Neuroscience #Linguistics #Psychology #FutureOfTech #AGI

References: arXiv:2508.20674

Disclaimer: The content on "Bridging Minds and Machines" was generated with the help of Gemini. Let us know in case of any gaps.

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