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Vectors of Cognitive AI: Attention

Panelists: michael graziano, jonathan cohen, vasudev lal, joscha bach.

The seminal contribution “Attention is all you need” (Vasvani et al. 2017), which introduced the Transformer algorithm, triggered a small revolution in machine learning. Unlike convolutional neural networks, which construct each feature out of a fixed neighborhood of signals, Transformers learn which data a feature on the next layer of a neural network should attend to. However, attention in neural networks is very different from the integrated attention in a human mind. In our minds, attention seems to be part of a top-down mechanism that actively creates a coherent, dynamic model of reality, and plays a crucial role in planning, inference, reflection and creative problem solving. Our consciousness appears to be involved in maintaining the control model of our attention.

In this panel, we want to discuss avenues into our understanding of attention, in the context of machine learning, cognitive science and future developments of AI.

Full program and references: https://cognitive-ai-panel.webflow.io/panels/attention

Meet The Titans: Google And OpenView (Microsoft) Faceoff On Chat Technology Innovation

With the heat of ChatGPT, the fastest growing app in the history of the web, no wonder Sundar Pichai, CEO of Google feels the need to enter with a challenge.

Google plans to release its most powerful and latest language model, LaMDA, as a companion to its search engine in weeks or in months. It will be interesting to see the trajectory comparatives between the two emerging Chat Titans.

Although Google’s forth quarter earnings call was done this week, Pichai said, “AI is the most profound technology we are working on today.” This is a pre-cursor announcement which will come shortly due to the momentum of OpenView’s GPT3.

What’s Next?: The 2023 Healthcare Industry Trend Report

In 2023, the US healthcare industry is again facing several significant challenges, including ongoing high inflation rates, labor shortages, and the persistent impact of the COVID-19 pandemic. Despite continued difficulties, leaders in the space are working to find innovative solutions to improve the current system while looking ahead at the promising future of medicine that appears to have already arrived.

From artificial intelligence-based medicine to breakthroughs in precision neuroscience, we outline key trends expected to shape the healthcare landscape in 2023 and beyond.

The 2023 Trend Report: Impactful Healthcare Innovations to Watch.

Engineering Cyborg Bacteria Through Intracellular Hydrogelation

Synthetic biology has made major strides towards the holy grail of fully programmable bio-micromachines capable of sensing and responding to defined stimuli regardless of their environmental context. A common type of bio-micromachines is created by genetically modifying living cells.[ 1 ] Living cells possess the unique advantage of being highly adaptable and versatile.[ 2 ] To date, living cells have been successfully repurposed for a wide variety of applications, including living therapeutics,[ 3 ] bioremediation,[ 4 ] and drug and gene delivery.[ 5, 6 ] However, the resulting synthetic living cells are challenging to control due to their continuous adaption and evolving cellular context. Application of these autonomously replicating organisms often requires tailored biocontainment strategies,[ 7-9 ] which can raise logistical hurdles and safety concerns.

In contrast, nonliving synthetic cells, notably artificial cells,[ 10, 11 ] can be created using synthetic materials, such as polymers or phospholipids. Meticulous engineering of materials enables defined partitioning of bioactive agents, and the resulting biomimetic systems possess advantages including predictable functions, tolerance to certain environmental stressors, and ease of engineering.[ 12, 13 ] Nonliving cell-mimetic systems have been employed to deliver anticancer drugs,[ 14 ] promote antitumor immune responses,[ 15 ] communicate with other cells,[ 16, 17 ] mimic immune cells,[ 18, 19 ] and perform photosynthesis.

7 ways to use ChatGPT at work to boost your productivity, make your job easier, and save a ton of time

Basically I underestimated chat gpt it is Basically much more powerful than I realized not just a Jetson society but it could even bring realities like we have seen in star trek the next generation where one can ask an AI anything and it can do anything given a task. This could also bring upon a superintelligence once programmed much like a wolfram alpha is for homework but for everything. It can nearly do any job and can replace all tech jobs eventually to get to universal basic income or even bring an end to the wild west of the internet it could create a near perfect cyber defense because it could simply know everything and make everything bug free. In short it can a near God like AI to answer and do any digital task. This can make nearly all jobs eventually automated:3.


It’ll be a while before ChatGPT takes your job entirely, and in the meantime you can use it to make work life easier.

The Future is Here: Top 10 Tech Predictions for 2100

Get a glimpse of the future and be amazed by the technological advancements that await us in the year 2100. Our video features top 10 predictions that will shape the world of technology in the next century. From fully immersive virtual reality to advanced artificial intelligence and nanotechnology, this video is packed with exciting insights.

We’ll dive into the possibilities of space colonization and teleportation, explore the potential of augmented reality and fusion energy, and look at the rise of robot assistants and mind uploading. Get ready to be amazed by the holographic displays that will take virtual experiences to a whole new level.

This video is perfect for anyone who wants to stay ahead of the curve and be informed about the future of technology. Subscribe now and turn on the notification bell to never miss an update. Optimize your viewing experience by turning on closed captions.

Leave a comment and let us know which prediction you’re most excited about. Join the discussion and share your thoughts on the future of technology. Don’t wait, watch now!

Generalist AI beyond Deep Learning

Generative AI represents a big breakthrough towards models that can make sense of the world by dreaming up visual, textual and conceptual representations, and are becoming increasingly generalist. While these AI systems are currently based on scaling up deep learning algorithms with massive amounts of data and compute, biological systems seem to be able to make sense of the world using far less resources. This phenomenon of efficient intelligent self-organization still eludes AI research, creating an exciting new frontier for the next wave of developments in the field. Our panelists will explore the potential of incorporating principles of intelligent self-organization from biology and cybernetics into technical systems as a way to move closer to general intelligence. Join in on this exciting discussion about the future of AI and how we can move beyond traditional approaches like deep learning!

Deepmind Ada brings foundation models to reinforcement learning

Deepmind’s AdA shows that foundation models also enable generalist systems in reinforcement learning that learn new tasks quickly.

In AI research, the term foundation model is used by some scientists to refer to large pre-trained AI models, usually based on transformer architectures. One example is OpenAI’s large language model GPT-3, which is trained to predict text tokens and can then perform various tasks through prompt engineering in a few-shot setting.

In short, a foundation model is a large AI model that, because of its generalist training with large datasets, can later perform many tasks for which it was not explicitly trained.

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