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24 May

NieR: Normal-Based Lighting Scene Rendering

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arXiv:2405.13097v1 Announce Type: new Abstract: In real-world road scenes, diverse material properties lead to complex light reflection phenomena, making accurate color reproduction crucial for enhancing the realism and safety of simulated driving environments. However, existing methods often struggle to capture the full spectrum of lighting effects, particularly in dynamic scenarios where viewpoint changes induce significant material color variations. To address this challenge, we introduce NieR (Normal-Based Lighting Scene Rendering), a novel framework that takes into account the nuances of light reflection on diverse material surfaces, leading to more precise rendering. To simulate the lighting synthesis process, we present the LD…

24 May

An Assessment of Model-On-Model Deception

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[Submitted on 10 May 2024] View a PDF of the paper titled An Assessment of Model-On-Model Deception, by Julius Heitkoetter and 2 other authors View PDF Abstract:The trustworthiness of highly capable language models is put at risk when they are able to produce deceptive outputs. Moreover, when models are vulnerable to deception it undermines reliability. In this paper, we introduce a method to investigate complex, model-on-model deceptive scenarios. We create a dataset of over 10,000 misleading explanations by asking Llama-2 7B, 13B, 70B, and GPT-3.5 to justify the wrong answer for questions in the MMLU. We find that, when models…

24 May

FasterViT for Semantic Segmentation

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In this article, we will modify the FasterViT model for semantic segmentation. FasterViT is a family of CNN-Transformer hybrid models for deep learning based computer vision tasks. The FasterViT models are faster and more accurate on several computer vision benchmarks, particularly the ImageNet dataset. We can also modify the model for semantic segmentation to get excellent results on a custom dataset. Although it is not straightforward and requires several changes to the architecture, it is possible. In this article, we will cover the architectural details and the changes we must make to the FasterViT model for semantic segmentation. Figure 1.…

24 May

Fujitsu Chosen For GENIAC Project To Enhance Reliability Of GenAI in Business Applications

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(issaro prakalung/Shutterstock) Fujitsu, one of the leading technology and business solutions providers, has been chosen for the research and development project for the enhanced infrastructures for post-5G information and communication systems. This project is part of the Generative AI Accelerator Challenge (GENIAC) initiative by Japan’s New Energy and Industrial Technology Development Organization (NEDO). The goal of the GENIAC project is to enhance Japan’s capabilities to harness the transformative power of GenAI by bringing together the knowledge of stakeholders in Japan and other countries. Fujitsu will be responsible for R&D on GenAI technologies with a focus on combining knowledge graphs with…

24 May

Data Machina #249

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Generative AI Music. In the last year or so, Generative AI Music has improved massively. Although early days, today you can generate some pretty decent, short duration music of all kinds with AI. If you like creating music and AI, here is a list of interesting Generative AI music stuff.Facebook AIR MusicGen. Probably one of the pioneering models in AI quality music generation. MusicGen has sparked a whole universe of MusicGen derivative models of all kinds, and it’s the model behind many musicgen apps. The model is based on a single stage auto-regressive Transformer model, and unlike Google LM, MusicGen…

24 May

Same AI + Different Deployment Plans = Different Ethics

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This month I will address an aspect of the ethics of artificial intelligence (AI) and analytics that I think many people don't fully appreciate. Namely, the ethics of a given algorithm can vary based on the specific scope and context of the deployment being proposed. What is considered unethical within one scope and context might be perfectly fine in another. I'll illustrate with an example and then provide steps you can take to make sure your AI deployments stay ethical. Why Autonomous Cars Aren't Yet Ethical For Wide Deployment There are limited tests of fully autonomous, driverless cars happening around…

24 May

How Real-World Enterprises are Leveraging Generative AI

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Generative AI (GenAI) is moving incredibly fast. So much so, that in less than two years, GenAI has emerged as one of the most exciting and transformative technologies, empowering enterprises across diverse industries to drive innovation, enhance productivity, and deliver exceptional customer experiences. At Databricks, we've seen exponential growth in the demand and development of GenAI applications across our platform from every sector of industry, be that communications, energy, financial services, healthcare and life sciences, manufacturing, public sector, media and entertainment, or retail and consumer goods.As we approach Data + AI Summit, we'll be bringing together a global community to…

24 May

Text Generation using GPT2

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The first ever GPT model was released by OpenAI in 2018. Since then, we have seen tremendous research and models based on the same architecture. Although GPT1 is old by today’s standards, GPT2 still holds fairly well for many fine-tuning tasks. In this article, we will dive into fine-tuning GPT2 for text generation. In particular, we will teach the model to generate detective stories based on Arthur Conan Doyle’s Sherlock Holmes series. Figure 1. Text generation example using the trained GPT2 model. GPTs and similar large language models can be fine-tuned for various text generation tasks. With this article, we…

24 May

Can Scale Become the ‘Data Foundry’ for AI?

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(DedMityay/Shutterstock) Scale AI, which provides data labeling and annotation software and services to organizations like OpenAI, Meta, and the Department of Defense, this week announced a $1-billion funding round at a valuation of nearly $14 billion, putting it in a prime position to capitalize on the generative AI revolution. Alexandr Wang founded Scale AI back in 2016 to provide labeled and annotated data, primarily for autonomous driving systems. At the time, self-driving vehicles seemed to be just around the corner, but getting the vehicles on the road in a safe manner has proven to be a tougher problem than originally…

23 May

Data Machina #250

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Llama 3: A Watershed AI moment? I reckon that the release of Llama 3 is perhaps one of the most important moments in AI development so far. The Llama 3 stable is already giving birth to all sorts of amazing animals and model derivatives. You can expect Llama 3 will unleash the mother of all battles against closed AI models like GPT-4.Meta AI just posted: ”Our largest Llama 3 models are over 400B parameters. And they are still being trained.” The upcoming Llama-400B will change the playing field for many independent researchers, little AI startups, one-man AI developers, and also…