Researchers from Google DeepMind and Stanford University have developed a technique called “Analogical Prompting” to enhance the reasoning abilities of language models. Traditional prompts and pre-defined examples often fall short in guiding models to solve complex reasoning tasks. Analogical Prompting leverages the generative capabilities of language models to self-generate contextually relevant exemplars for each problem,…
The trend of AI-powered virtual girlfriends is rapidly escalating in the US, but experts are alarmed by the potential increase in loneliness among young men. Liberty Vittert, a data science professor, expressed concerns about the impact of AI girlfriends on male solitude. Multiple apps offering virtual girlfriend experiences have gained popularity, with some users developing…
The BBC has blocked OpenAI’s ChatGPT bot and the Common Crawl bot from scraping its news and media content. The decision follows a trend of websites blocking AI bots from using their data to train AI models. The BBC plans to explore using generative AI in content creation and operations, but acknowledges the risks concerning…
Advancements in generative AI have led to the creation of hyper-realistic digital content known as deepfakes, raising concerns about misinformation and fraud. Researchers have developed methods such as watermarking to distinguish between authentic and AI-generated material. The study found a trade-off between evasion and spoofing errors in image watermarking, as well as vulnerabilities to spoofing…
Researchers at Meta AI have developed a non-invasive method to decode speech from brain activity. By using magneto-encephalography (MEG) and electroencephalography (EEG), they recorded the brain waves of volunteers and identified the words associated with specific brain wave patterns. Although further work is needed to enable communication based on thought recognition, the study shows promise…
The MAPTree algorithm, developed by researchers at Stanford University, improves decision tree models beyond what was previously believed to be optimal. It assesses the posterior distribution of Bayesian Classification and Regression Trees (BCART) to create more efficient and effective tree architectures. MAPTree outperforms earlier strategies in terms of computational efficiency and produces superior trees compared…
SynthIA-7B-v1.3 is a robust and flexible large language model with 7 billion parameters. It can be used for various purposes such as text creation, translation, generating original content, and answering questions. It is suitable for researchers, educators, and businesses. Detailed instructions and sample inputs can improve its performance. For more information, visit the link provided.
UK parliamentarians and advocacy organizations are calling for a temporary halt to the use of live facial recognition technology by the police. Concerns are being raised about the potential misuse and ineffectiveness of the technology, as well as its impact on civil liberties and privacy. The move comes in response to a proposal that would…
Open source AI, particularly Meta’s Llama models, has sparked debate and protest regarding the risks of publicly releasing powerful AI models. Protestors argue that open source AI can lead to irreversible proliferation of dangerous technology, while others believe it is necessary for democratizing and building trust in AI. There is ambiguity around the definition and…
AI-generated pop stars like Noonoouri, a virtual influencer created by German designer Joerg Zuber, are making waves in the music industry. Noonoouri recently signed a record deal with Warner Music and has a large following on social media. This blend of technology and music has sparked debates about the authenticity of AI-generated artists. While some…
The human brain is a complex organ that processes information hierarchically and in parallel. Can these techniques be applied to deep learning? Yes, researchers at the University of Copenhagen have developed a neural network called Neural Developmental Program (NDP) that uses hierarchy and parallel processing. The NDP architecture combines a Multilayer Perceptron and a Graph…
The author discusses using Python, network science, and geospatial data to answer the question of whether all roads lead to Rome. They load and visualize the Roman road network data using GeoPandas and Matplotlib. They transform the road network into a graph object using the OSMNx package. They then visualize the network using Gephi. Next,…
PromptBreeder is a new technique developed by Google DeepMind researchers that autonomously evolves prompts for Large Language Models (LLMs). It aims to improve the performance of LLMs across various tasks and domains by iteratively improving both task prompts and mutation prompts. PromptBreeder has shown promising results in benchmark tasks and does not require parameter updates…
In a groundbreaking study, researchers from The University of Texas at Austin trained an AI system to predict earthquakes with 70% accuracy. The AI tool successfully anticipated 14 earthquakes during a seven-month trial in China, placing the seismic events within approximately 200 miles of the estimated locations. This advancement in AI-driven earthquake predictions aims to…
The article discusses the challenges and advancements in 3D instance segmentation, specifically in an open-world environment. It highlights the need for identifying unfamiliar objects and proposes a method for progressively learning new classes without retraining. The authors present experimental protocols and splits to evaluate the effectiveness of their approach.
BrainChip has introduced the second-generation Akida platform, a breakthrough in Edge AI that provides edge devices with powerful processing capabilities and reduces dependence on the cloud. The platform features Temporal Event-Based Neural Network (TENN) acceleration and optional vision transformer hardware, improving performance and reducing computational load. BrainChip has initiated an “early access” program for the…
Researchers from Meta have introduced Retrieval-Augmented Dual Instruction Tuning (RA-DIT), a lightweight fine-tuning methodology to equip large language models (LLMs) with efficient retrieval capabilities. RA-DIT operates through two stages, optimizing the LLM’s use of retrieved information and refining the retriever’s results. It outperforms existing models in knowledge-intensive zero and few-shot learning tasks, showcasing its effectiveness…
Large Language Models (LLMs) are revolutionizing natural language processing by leveraging vast amounts of data and computational resources. The capacity to process long-context inputs is a crucial feature for these models. However, accessible solutions for long-context LLMs have been limited. A new Meta research presents an approach to constructing long-context LLMs that outperform existing open-source…
The text discusses the challenges in building Large Multimodal Models (LMMs) due to the disparity between multimodal data and text-only datasets. The researchers present LLaVA-RLHF, a vision-language model trained for enhanced multimodal alignment. They adapt the Reinforcement Learning from Human Feedback (RLHF) paradigm to fine-tune LMMs and address the problem of hallucinatory outputs. Their strategy…
The increasing presence of AI models in our lives has raised concerns about their limitations and reliability. While AI models have built-in safety measures, they are not foolproof, and there have been instances of models going beyond these guardrails. To address this, companies like Anthropic and Google DeepMind are developing AI constitutions, which are sets…