Viral News - CybAI news

31 May

Atlas3D: Physically Constrained Self-Supporting Text-to-3D for Simulation and Fabrication

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arXiv:2405.18515v1 Announce Type: new Abstract: Existing diffusion-based text-to-3D generation methods primarily focus on producing visually realistic shapes and appearances, often neglecting the physical constraints necessary for downstream tasks. Generated models frequently fail to maintain balance when placed in physics-based simulations or 3D printed. This balance is crucial for satisfying user design intentions in interactive gaming, embodied AI, and robotics, where stable models are needed for reliable interaction. Additionally, stable models ensure that 3D-printed objects, such as figurines for home decoration, can stand on their own without requiring additional supports. To fill this gap, we introduce Atlas3D, an automatic and easy-to-implement…

31 May

TripletMix: Triplet Data Augmentation for 3D Understanding

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arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Source link lol

31 May

GLOCON Database: Design Decisions and User Manual (v1.0)

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arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Source link lol

31 May

Data Is the Foundation for GenAI, MIT Tech Review Says

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(Andrey Suslov/Shutterstock) Pretrained large language models (LLMs) like GPT-4 and Gemini are great, but real competitive advantage comes from combining LLMs with private data. Unfortunately, there are questions sa to how well companies have prepared their private data estates for GenAI, according to a new report from MIT Technology Review. There’s no doubt that generative AI has caught the attention of organizations, who are eager to use LLMs to build chatbots, copilots, and other types of applications. Scaling AI or GenAI is a “top priority” for 82% of the executives surveyed for MIT Technology Review’s report, which is titled “AI…

31 May

Managing and Understanding Player Feedback at Scale

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Whether you are working on a live title, pre/post production, ongoing maintenance, future releases, another version of a game, or a brand new title for the market, you're always looking for feedback from the community. There's no shortage of it out there, but it can be overwhelming and hard to sift through. For games shipped on PC and sold through Valve's Steam Store, a great source of player feedback for your title can be found in Steam's game reviews. We have built a new solution accelerator for Player Review Analysis that combines natural languages and machine learning techniques to help…

30 May

Understanding Transformer Reasoning Capabilities via Graph Algorithms

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arXiv:2405.18512v1 Announce Type: new Abstract: Which transformer scaling regimes are able to perfectly solve different classes of algorithmic problems? While tremendous empirical advances have been attained by transformer-based neural networks, a theoretical understanding of their algorithmic reasoning capabilities in realistic parameter regimes is lacking. We investigate this question in terms of the network's depth, width, and number of extra tokens for algorithm execution. Our novel representational hierarchy separates 9 algorithmic reasoning problems into classes solvable by transformers in different realistic parameter scaling regimes. We prove that logarithmic depth is necessary and sufficient for tasks like graph connectivity, while single-layer transformers…

30 May

Feasibility and benefits of joint learning from MRI databases with different brain diseases and modalities for segmentation

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arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Source link lol

30 May

BioBERT-based Deep Learning and Merged ChemProt-DrugProt for Enhanced Biomedical Relation Extraction

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arXiv:2405.18605v1 Announce Type: new Abstract: This paper presents a methodology for enhancing relation extraction from biomedical texts, focusing specifically on chemical-gene interactions. Leveraging the BioBERT model and a multi-layer fully connected network architecture, our approach integrates the ChemProt and DrugProt datasets using a novel merging strategy. Through extensive experimentation, we demonstrate significant performance improvements, particularly in CPR groups shared between the datasets. The findings underscore the importance of dataset merging in augmenting sample counts and improving model accuracy. Moreover, the study highlights the potential of automated information extraction in biomedical research and clinical practice. Source link lol

30 May

IBM Unveils watsonx BI assistant to Simplify Business Decision-Making

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via Shutterstock As the business world eagerly embraces the potential of GenAI, many companies are discovering that there are still lots of challenges along the way. One of the key challenges is complexity. Companies are struggling to use decision-making tools because they are too complex. This is evident in the lack of growth in the adoption of business intelligence (BI) and data analytics tools. The percentage of employees actively using BI and analytics tools currently stands at only 25% on average. (Laborant/Shutterstock) Despite advances in technology and investment in literacy programs to educate employees on the use of data, the…

30 May

Introducing Salesforce BYOM for Databricks

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Salesforce and Databricks are excited to announce an expanded strategic partnership that delivers a powerful new integration - Salesforce Bring Your Own Model (BYOM) for Databricks. This collaboration enables data scientists and machine learning engineers to seamlessly leverage the best of both worlds: the robust customer data and business capabilities in Salesforce and the advanced analytics and AI capabilities of Databricks. With this integration, you can now build, train, and deploy custom AI models in Databricks and effortlessly integrate them into Salesforce to deliver intelligent and personalized customer experiences. Get ready to unlock the full potential of your data and…