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15+ AI Tools For Developers (December 2023)
This article lists over 15 AI tools for developers as of December 2023, highlighting their key features. These tools assist in coding, debugging, generating documentation, managing snippets, creating AI agents, designing visuals, and more. They include GitHub Copilot, Amazon CodeWhisperer, Notion AI, Stepsize, Mintlify, Pieces for Developers, LangChain, You.com, AgentGPT, Jam.dev, Durable, Leap AI, AssemblyAI,…
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Roadmap for Transitioning to Data Analytics
To transition to data analytics from another field, pursue relevant education or training, gain practical experience, and engage with the data science community through platforms like Towards Data Science.
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How Getir reduced model training durations by 90% with Amazon SageMaker and AWS Batch
Getir, established in 2015, is a leading ultrafast grocery delivery company with a multinational presence. Utilizing Amazon SageMaker and AWS Batch, they reduced model training time by 90% and improved operational efficiency. Their data science team developed a product category prediction pipeline with an 80% accuracy rate, aiding commercial teams in inventory management and competitive…
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Asking ChatGPT to repeat words can expose its training data
Researchers discovered that language models like GPT-3.5 Turbo could inadvertently reveal their training data when prompted to repeat simple words, leaking sensitive content, personal information, and copyrighted material. The technique, known as a divergence attack, had a success rate of 3% and poses a significant security risk. Companies have been notified, with the web version…
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New AI Video App by Pika Labs Makes a Big Splash, Boosts Chinese Company’s Stock
Pika Labs, an AI video generator startup, has caused a stir with its product, Pika 1.0, leading to a stock increase for Sunyard Technology, a firm with familial ties to co-founder Demi Guo. The startup raised $55 million and aims to democratize video creation, despite broader industry challenges.
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Meet PepCNN: A Deep Learning Tool for Predicting Peptide Binding Residues in Proteins Using Sequence, Structural, and Language Model Features
Developed by an international research team, PepCNN is a deep learning model that predicts protein-peptide binding with higher accuracy than previous tools. Using structural, sequence, and language model features, it excels in specificity, precision, and AUC metrics for better drug discovery and understanding protein-peptide interactions. Further improvements are planned using DeepInsight technology.
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Breaking the Boundaries in 3D Scene Representation: How a New AI Technique is Changing the Game with Faster, More Efficient Rendering and Reduced Storage Demands
NeRF models scenes in 3D and learns from various viewpoints to create photorealistic images. Researchers from Sungkyunkwan University improved efficiency with a mask strategy, reducing memory requirements and increasing speed. Point-based rendering enhancements and ongoing research promise to further advance realistic 3D applications. Credit goes to the researchers and is shared via various online AI…
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Meet Meditron: A Suite of Open-Source Medical Large Language Models (LLMs) based on LLaMA-2
Researchers released MediTron, an open-source medical LLM suite with 7B and 70B parameter variants, excelling in benchmarks and tailored for tasks like medical QA. It uses an extensive medical dataset for training but requires further testing before clinical deployment to ensure safety.
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Microsoft Researchers Propose MAIRA-1: A Radiology-Specific Multimodal Model for the Task of Generating Radiological Reports from Chest X-rays (CXRs)
Microsoft researchers developed MAIRA-1, a model combining a chest X-ray-specific image encoder with a fine-tuned language model to generate accurate radiology reports. It leverages data augmentation and evaluation metrics tailored to clinical relevance to improve report quality. Future enhancements may include incorporating study histories to reduce inaccuracies.
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This AI Paper from Northeastern University and MIT Develop Interpretable Concept Sliders for Enhanced Image Generation Control in Diffusion Models
Researchers from Northeastern University, MIT, and an independent researcher developed Concept Sliders for text-to-image diffusion models, allowing fine-grained image control and editing. This method enables manipulation of visual concepts that are usually hard to describe in words and offers a practical, disentangling solution for more precise image customization through open-source code and trained sliders.