Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: robotics/AI – Page 238

Why AI Is A Philosophical Rupture

Be that as it may, there is nothing much symbolic here. At least not in the classical sense of the term.

I am emphasizing this absence of the symbolic because it is a beautiful way to show that deep learning has led to a pretty powerful philosophical rupture: Implicit in the new concept of intelligence is a radically different ontological understanding of what it is to be human, indeed, of what reality is or of how it is structured and organized.

Understanding this rupture with the older concept of intelligence and ontology of the human/the world is key, I think, to understanding your actual question: Are we entering what you call a new AIxial age, where AI will amount to something similar to what writing amounted to roughly 3,000 to 2,000 years ago?

Direct Solar Power Prediction from Machine Learning

How can machine learning help determine the best times and ways to use solar energy? This is what a recent study published in Advances in Atmospheric Sciences hopes to address as a team of researchers from the Karlsruhe Institute of Technology investigated how machine learning algorithms can be used to predict and forecast weather patterns to enable more cost-effective approaches for using solar energy. This study has the potential to help enhance renewable energy technologies by fixing errors that are often found in current weather prediction models, leading to more efficient use of solar power by predicting when weather patterns will enable the availability of the Sun for solar energy needs.

For the study, the researchers used a combination of statistical methods and machine learning algorithms to help predict the most efficient times of day that photovoltaic (PV) power generation will achieve maximum production output. Their methods used what’s known as post-processing, which involves correcting weather forecasting errors before that data enters PV models, resulting in changing PV model predictions, resulting in establishing more accurate weather forecasting from machine learning algorithms.

“One of our biggest takeaways was just how important the time of day is,” said Dr. Sebastian Lerch, who is a professor at the Karlsruhe Institute of Technology and a co-author on the study. “We saw major improvements when we trained separate models for each hour of the day or fed time directly into the algorithms.”

Addressing the use of generative AI in academic writing

The rise of generative AI has been a major disruptive force in academia. Academics are concerned about its impact on student learning. Students can use generative AI technologies, such as ChatGPT, to complete many academic tasks on their behalf. This could lead to poor academic outcomes as students use ChatGPT to complete assessments, rather than engaging with the learning material. One particularly vulnerable academic activity is academic writing. This paper reports the results of an active learning intervention where ChatGPT was used by students to write an academic paper. The resultant papers were then analysed and critiqued by students to highlight the weaknesses of such AI-produced papers. The research used the Technology Acceptance Model to measure changing student perceptions about the usefulness and ease of use of ChatGPT in the creation of academic text.

The NanoBots Are Coming, How Will They Affect Us In The Future?

Go to https://historicmail.com/DROID and check out with code DROID to get 10% off on their Christmas Sale on your gifts and help support the channel. Thanks to Historic Mail for sponsoring this video!
Machines so tiny they would be far smaller than a human blood cell, this is the promise of nanotechnology, and they already exist but how are they even made and will they be scarier than A.I. Experts say that we are just at the beginning of the nanobot revolution and what they promise could little short of miraculous. In this video we look at how we got here and what the current state of the art is.

To give one off tips and donations please use the following :
https://www.buymeacoffee.com/curiousdroid.

Patreon : https://www.patreon.com/curiousdroid — For longer term channel support.

Paypal.me : https://paypal.me/curiousdroid — For 1 off direct tips and thank you payments.

Facebook : https://www.facebook.com/curiousdroid.

Quote: “We are like butterflies who flutter for a day and think it’s forever” : Carl Sagan.

Continue reading “The NanoBots Are Coming, How Will They Affect Us In The Future?” | >

A framework for soft mechanism driven robots

Soft robots excel in safety and adaptability, yet their lack of structural integrity and dependency on open-curve movement paths restrict their dexterity. Conventional robots, albeit faster due to sturdy locomotion mechanisms, are typically less robust to physical impact. We introduce a multi-material design and printing framework that extends classical mechanism design to soft robotics, synergizing the strengths of soft and rigid materials while mitigating their respective limitations. Using a tool-changer equipped with multiple extruders, we blend thermoplastics of varying Shore hardness into monolithic systems. Our strategy emulates joint-like structures through biomimicry to achieve terrestrial trajectory control while inheriting the resilience of soft robots. We demonstrate the framework by 3D printing a legged soft robotic system, comparing different mechanism syntheses and material combinations, along with their resulting movement patterns and speeds. The integration of electronics and encoders provides reliable closed-loop control for the robot, enabling its operation across various terrains including sand, soil, and rock environments. This cost-effective framework offers an approach for creating 3D-printed soft robots employable in real-world environments.

Soft mechanism driven robots, made via multi-material 3D printing, combine soft and rigid components for robust, adaptable locomotion. This framework balances flexibility and strength, enabling effective operation across varied terrains.

Sam Altman Announces GPT-5 Timeline Update, Cancels o3 As Standalone Model

In today’s AI news, OpenAI will ship GPT-5 in a matter of months and streamline its AI models into more unified products, said CEO Sam Altman in an update. Specifically, Altman says the company plans to launch GPT-4.5 as its last non-chain-of-thought model and integrate its latest o3 reasoning model into GPT-5.

In other advancements, Harvey, a San Francisco AI startup focused on the legal industry, has raised $300 million in a funding round led by Sequoia that values the startup at $3 billion — double the amount investors valued it at in July. The Series D funding round builds on the momentum and reflects investors’ enthusiasm for AI tools …

Meanwhile, Meta is in talks to acquire South Korean AI chip startup FuriosaAI, according to people familiar with the matter, a deal that could boost the social media giant’s custom chip efforts amid a shortage of Nvidia chips and a growing demand for alternatives. The deal could be completed as early as this month.

Then, AI took another step into Hollywood today with the launch of a new filmmaking tool from showbiz startup Flawless. The product — named DeepEditor — promises cinematic wizardry for the digital age. For movie makers, the tool offers photorealistic edits without a costly return to set.

In videos, join IBM’s Boris Sobolev as he explains how model customization can enhance reliability and decision-making of agentic systems. Discover practical tips for data collection, tool use, and pushing the boundaries of what your AI can achieve. Supercharge your AI agents for peak performance!

CEO and cofounder Andrew Feldman about his startup Then, Moderator Marc Pollefeys (Professor of Computer Science at ETH Zurich and Director of the Microsoft Mixed Reality and AI Lab in Zurich) leads an expert panel. The discussion will focus on advancements in robotics and the impact of embodied AI in complex, real-world scenarios. Speakers include; Marco Hutter (Director of the Robotic Systems Lab at ETH and Senior Director of Research at the AI Institute) Péter Fankhauser (Co-Founder & CEO at ANYbotics) Raquel Urtasun (Founder & CEO at Waabi and Professor of Computer Science at the University of Toronto).

We close out with, Databricks CEO Ali Ghodsi speaks exclusively with Worldwide Exchange Anchor Frank Holland about the new partnership announced on Thursday between the data analytics startup and the European tech giant.

Continue reading “Sam Altman Announces GPT-5 Timeline Update, Cancels o3 As Standalone Model” | >

Utility Engineering

As AIs rapidly advance and become more agentic, the risk they pose is governed not only by their capabilities but increasingly by their propensities, including goals and values. Tracking the emergence of goals and values has proven a longstanding problem, and despite much interest over the years it remains unclear whether current AIs have meaningful values. We propose a solution to this problem, leveraging the framework of utility functions to study the internal coherence of AI preferences. Surprisingly, we find that independently-sampled preferences in current LLMs exhibit high degrees of structural coherence, and moreover that this emerges with scale. These findings suggest that value systems emerge in LLMs in a meaningful sense, a finding with broad implications. To study these emergent value systems, we propose utility engineering as a research agenda, comprising both the analysis and control of AI utilities. We uncover problematic and often shocking values in LLM assistants despite existing control measures. These include cases where AIs value themselves over humans and are anti-aligned with specific individuals. To constrain these emergent value systems, we propose methods of utility control. As a case study, we show how aligning utilities with a citizen assembly reduces political biases and generalizes to new scenarios. Whether we like it or not, value systems have already emerged in AIs, and much work remains to fully understand and control these emergent representations.

/* */