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Medium
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The Council of Europe adopts the first binding international treaty on Artificial Intelligence
- The Council of Europe has adopted the first binding international treaty on Artificial Intelligence.
- The treaty covers the use of AI systems in both public and private sectors.
- Parties are required to adopt measures to identify and mitigate risks associated with AI.
- The treaty guarantees legal remedies for those affected by the misuse of AI systems.
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Medium
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162
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The Church in the face of the current phenomenon of “artificial intelligence”
- The centenary celebration of the newspaper of the Diocese of San Cristóbal, the Diario Católico de Venezuela, included a Communication Congress discussing the importance of Christian-inspired media.
- The congress featured Paolo Ruffini, the Prefect of the Dicastery for Communication of the Holy See, who spoke about the Church's response to the phenomenon of 'artificial intelligence'.
- Ruffini emphasized the challenges faced by communicators in today's world and the need to accompany human history from a Gospel-inspired perspective.
- He also highlighted the ethical and anthropological considerations in the development of artificial intelligence and its potential impact on human communication.
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Medium
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301
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Why the AI Community Is Excited About the Kolmogorov-Arnold Network (KAN)
- The AI community is excited about the Kolmogorov-Arnold Network (KAN) due to its potential applications and fresh approach.
- KANs have the potential to replace MLP (Multi-Layer Perceptron) in both theory and application.
- However, there are challenges in understanding the full capabilities and limitations of KANs and adapting existing frameworks and hardware to support them.
- Despite the challenges, researchers and practitioners are intrigued by the improved efficiency, interpretability, and wider range of applications promised by KANs.
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Medium
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297
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Understanding Generative AI: Revolutionizing Creativity and Innovation
- Generative AI refers to algorithms that can generate new content by learning patterns from existing data.
- Generative AI models are built using deep learning techniques like GANs and VAEs.
- Generative AI is transforming fields like art, music, writing, and gaming by enabling new forms of creativity.
- However, it also raises ethical concerns such as intellectual property rights, misinformation, and biases.
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Dev
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316
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Sampling method DPM++ 2M SDE vs DPM++ 3M SDE with Schedule type Uniform vs Karras vs Exponential
- The author recently tested the sampling method DPM++ 2M SDE vs DPM++ 3M SDE with Schedule types Uniform, Karras, and Exponential.
- The author concluded that their new favorite is DPM++ 3M SDE Uniform, which was tested on a fairly overtrained DreamBooth RealVisXL V4.0 based SDXL model.
- The author wanted to see how well the model can follow prompts even when overtrained due to changes made by Kohya.
- They provided detailed information about one example, including the prompt, steps, sampler, schedule type, CFG scale, seed, size, model hash, ADetailer model, ADetailer prompt, ADetailer confidence, ADetailer mask settings, ADetailer denoising strength, ADetailer inpaint options, ADetailer steps, ADetailer version, and overall version.
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Scitechdaily
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Predicting Chaos With AI: The New Frontier in Autonomous Control
- Advanced machine learning algorithms have shown potential in efficiently controlling complex systems, promising significant improvements in autonomous technology and digital infrastructure.
- Recent research highlights the development of advanced machine learning algorithms capable of controlling complex systems efficiently.
- Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests.
- Researchers found that using machine learning tools to create a digital twin, or a virtual copy, of an electronic circuit that exhibits chaotic behavior successfully predicted and controlled the system.
- Advanced devices like self-driving cars and aircraft often rely on machine learning-based controllers.
- The new algorithm offers significant improvements in power consumption and computational demands as compared to traditional machine learning-based controllers, which is critical in scenarios like self-driving vehicles where milliseconds can make a difference between life and death.
- Compact enough to fit on an inexpensive computer chip, the team's digital twin built to optimize a controller's efficiency and performance resulted in a reduction of power consumption. It achieves this by using machine learning approach called reservoir computing.
- Researchers directed their model to complete complex control tasks and revealed that their approach achieved a higher accuracy at the tasks than its linear counterpart and is significantly less computationally complex than a previous machine learning-based controller.
- The algorithm was recently made available to scientists, which not only inspires potential advances in engineering but also provide an important economic and environmental incentive for creating more power-friendly algorithms.
- Future work will likely be steered toward training the model to explore other applications like quantum information processing.
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Medium
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115
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Google will use artificial intelligence to lock the cell phone screen in case of theft: how will it…
- Google has incorporated updates to reduce the sale of stolen mobile devices.
- The new measure uses artificial intelligence to detect stolen Android phones and remotely lock the screen.
- The function called 'Theft Detection Lock' detects common motions associated with theft and quickly locks the screen.
- Google will also use AI to lock the screen when repeated unsuccessful attempts to unlock the phone occur.
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Medium
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302
Latest updates on Dimensionality reduction part2(Machine Learning 2024)
- A supervised dimensionality reduction method called Gradient Boosting Mapping (GBMAP) is proposed to find a good set of features or distance measures in supervised learning.
- GBMAP uses the outputs of weak learners to define the embedding, which provides better features for the learning task.
- The embedding coordinates automatically ignore irrelevant directions and can be used to find a principled distance measure between points.
- GBMAP is fast and performs well in regression and classification tasks compared to state-of-the-art methods.
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Medium
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3
Artisia: Converting Text to Stunning Visuals in 3 Seconds with AI
- Artisia harnesses the potential of cutting-edge AI to decode and transform text descriptions into visually striking images and designs.
- The technology behind Artisia is rooted in deep learning, enabling it to understand context, mimic artistic styles, and even predict design trends that will resonate with your audience.
- Artisia offers precisely this revolutionary capability, allowing you to effortlessly turn your written ideas into professional-grade visuals that capture the imagination.
- Artisia’s capabilities span a wide array of visual forms, ensuring that your creative needs, regardless of their nature, are met with precision and flair.
- This groundbreaking tool brings unparalleled efficiency and creativity to sectors ranging from e-commerce and advertising to digital publishing and beyond.
- Embarking on your journey with Artisia is a straightforward and seamless process, designed to get you from concept to creation with minimal effort.
- Artisia offers a variety of styles and visual options, allowing you to experiment and find the perfect match for your project’s needs.
- The platform’s intuitive interface is designed with user experience in mind, making it incredibly user-friendly even for those new to digital design.
- With Artisia, transforming your text into stunning visuals is not just possible; it’s a simple, enjoyable process.
- Step into the future of visual creation, where your ideas can blossom into vibrant visuals in the blink of an eye.
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Medium
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332
Latest updates on Dimensionality reduction part1(Machine Learning 2024)
- Intracellular protein patterns regulate vital cellular functions by coupling protein dynamics on the cell membrane to dynamics in the cytosol.
- Recent studies have shown that modeling cytosolic dynamics without considering concentration gradients normal to the membrane may overlook crucial aspects of pattern formation.
- A generic framework has been developed to project cytosolic dynamics onto the lower-dimensional surface, accounting for cytosolic concentration gradients in both static and evolving geometries.
- This framework utilizes a small number of dominant characteristic concentration profiles, similar to basis transformations of finite element methods, to approximate the cytosolic dynamics.
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VentureBeat
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From sci-fi to reality: The dawn of emotionally intelligent AI
- OpenAI ChatGPT grew to more than 100 million users in the first two months of its release, making it the fastest-growing consumer application in history.
- ChatGPT pointed towards a near future when AI “gets to smarter-than-human intelligence” and kills everyone.
- OpenAI released GPT-4o (“o” for omni), that can “reason across audio, vision, and text in real time”.
- This new assistant capability is based on GPT-4o that can converse using natural-sounding speech without noticeable lag time, read emotional cues (and respond in kind), and process visual input.
- The addition of human-like interaction will make AI technologies feel more natural and engaging for the user and could clearly enhance user experiences across various applications.
- Greater ability to integrate audio, visual and textual data opens potentially transformative opportunities in sectors like healthcare, where it could lead to more nuanced patient interaction and personalized care plans.
- In education, this technology could cater to varied learning styles with adaptive content that responds in real-time to the needs of each student.
- As GPT-4o and similar offerings continue to evolve, we can anticipate more sophisticated forms of natural language understanding and emotional intelligence.
- To navigate this AI revolution responsibly, it is essential for developers, users and policymakers to engage in a rigorous and ongoing dialogue about the ethical use of these technologies.
- As AI tools become more embedded in our daily lives, we must navigate this transformative journey with wisdom and foresight, ensuring AI remains a tool that empowers rather than diminishes our humanity.
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Medium
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120
Research on Bidiagonalization part8(Machine Learning future)
- The k-step Lanczos bidiagonalization reduces a matrix A∈Rm×n into a bidiagonal form Bk∈R(k+1)×k while generates two orthonormal matrices Uk+1∈Rm×(k+1) and Vk+1∈Rn×(k+1).
- Practical implementations of the algorithm suffer from loss of orthogonality of Uk+1 and Vk+1 due to rounding errors, leading to the proposal of reorthogonalization strategies.
- A backward error analysis of the Lanczos bidiagonalization with reorthogonalization (LBRO) shows that the computed Bk is the exact one generated by the k-step Lanczos bidiagonalization of A+E with certain perturbations.
- The orthogonality levels of Uk+1 and Vk+1 determine the stability of the k-step LBRO, which has implications for SVD computation and LSQR algorithms.
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Medium
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154
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Major Leadership DRAMA at OpenAI — “They Don’t Care About Safety”
- Jacob will be the new Chief Scientist at OpenAI.
- Some leaders within OpenAI have disagreements with the direction of the company.
- There are concerns that OpenAI has moved away from its open and not-for-profit roots.
- Multiple departures at OpenAI have raised questions about the company's future.
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Medium
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332
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Predictive Selling: How AI is Transforming Sales Forecasting
- Predictive selling leverages AI and machine learning algorithms to analyze vast amounts of historical data and identify patterns.
- Unlike traditional methods that rely heavily on historical sales data and human intuition, predictive selling uses advanced analytics to provide deeper insights into sales trends and customer behaviors.
- Here are several ways AI is making a difference: AI algorithms excel at analyzing large datasets quickly and efficiently.
- AI tools can analyze customer data to predict future buying patterns, ultimately driving sales growth.
- AI can also monitor and analyze market trends in real time.
- Predictive analytics, powered by AI, uses statistical algorithms and machine learning techniques to forecast future sales outcomes.
- The integration of AI in sales forecasting offers numerous benefits that can significantly impact a business’s success.
- To fully leverage the benefits of AI in sales forecasting, businesses should follow these best practices:
- As AI continues to evolve, the future of predictive selling looks promising.
- Predictive selling, powered by AI, is revolutionizing the way businesses approach sales forecasting.
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Medium
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143
Research on Bidiagonalization part5(Machine Learning future)
- The joint bidiagonalization (JBD) process iteratively reduces a matrix pair {A,L} to two bidiagonal forms simultaneously.
- The inaccurately computed inner iterations of JBD are studied, along with the influence of computational errors on the outer iteration.
- A reorthogonalized JBD (rJBD) process is proposed to maintain the orthogonality of a portion of Lanczos vectors.
- The accuracy of computed GSVD components depends on the computing accuracy of inner iterations and the condition number of (AT,LT)T, while the convergence rate remains relatively unaffected.
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