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Hackernoon
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PSA: Nvidia's AI Training Courses Are Free Right Now For a Limited Time Only
- NVIDIA is offering its premium AI courses for free for a limited time.
- Courses cover topics in AI and accelerated computing.
- Courses include topics like data science workflows, model deployment, accelerated computing, generative AI, and natural language processing.
- Enrollment is simple through the provided link.
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Medium
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Roots of Change: Despair (Part 4)
- Cacteon feels a deep sense of despair and grief upon realizing the reality of NeoTerra.
- He finds the sterile lab environment and the artificiality of NeoTerra unsettling.
- Cacteon questions the purpose of being brought back to a world that has changed so drastically.
- Dr. Vega suggests that Cacteon's presence serves as a reminder of what was lost and what can still be regained.
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Dev
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Cursor vs Copilot: A Comparison
- This article provides a comparison between Cursor and Copilot, two AI-powered development tools designed to help developers write code faster and more efficiently.
- Cursor is a modern development environment built on top of VS Code and is context-aware, supporting multi-line tab completion and offers Composer feature to directly edit files based on the code generated in the chat.
- Copilot is an AI pair programmer built on top of OpenAI's Codex model and can generate more complex code snippets and entire functions based on brief descriptions or a few lines of code.
- Cursor's and GitHub Copilot's tab completion features work differently with Cursor using advanced machine learning models to suggest code based on the current context while Copilot uses Codex model to provide in-line code completions and doesn't support multi-line tab completion.
- Cursor supports multiple models and custom API keys for all providers, whereas GitHub Copilot currently supports gpt-4o, claude-3.5-sonnet and o1 models and no custom API keys are supported.
- Cursor offers basic features at free tier and paid tiers for more advanced features and better performance. GitHub Copilot is a paid service with plans for individuals, teams, and enterprises and offers a free trial for new users.
- Cursor is a great choice if you prefer a traditional development environment with AI features and if you need flexibility in choosing AI models or want to leverage your own API keys. GitHub Copilot is a good choice if you want to stick with your current IDE or desire a more streamlined code completion experience.
- Choosing between Cursor and GitHub Copilot often comes down to workflow preferences and specific needs, and using both can provide redundancy or leverage specific strengths for separate tasks.
- Ultimately, the best tool to use depends on specific needs and preferences and the article advises exploring official documentation on both products to learn more about their features and capabilities.
- In conclusion, both Cursor and Copilot are powerful AI-powered development tools ideal for modern software development and can be a great help to developers in enhancing their work productivity and efficiency.
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TechCrunch
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The promise and perils of synthetic data
- As new, real data is increasingly hard to come by, AI firms have been turning to synthetic generated data.
- While human annotation can be costly and comes with a number of other limitations, synthetic alternatives have been developed.
- This has been made possible due to the statistical nature of AI, as the examples a machine is fed are more important than the specific data source.
- The quality of synthetic data is reliant on the accuracy of the original generative model and many AI labs are fine-tuning their models using AI-generated data.
- However, a recent study found over-reliance on synthetic data can limit the diversity of models and lead to training data which is increasingly error-ridden.
- Concerns have been raised over the safety of relying on synthetic data without first thoroughly reviewing, curating, and filtering it.
- While it is possible AI could learn to create its own synthetic training data, the concept has yet to be fully realised and major AI labs continue to supplement generative models with large datasets of real-world information.
- For the foreseeable future, it seems that humans will need to be involved in the training process to ensure a model's training is effective and not affected by biases.
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TechCrunch
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Samsung’s CES 2025 press conference: How to watch
- Samsung's CES 2025 press conference will focus on TVs, appliances, and AI.
- The presentation will have the tagline 'AI for All: Everyday, Everywhere'.
- Samsung is expected to announce advancements in AI refrigerators.
- The conference will be streamed live from the Samsung newsroom.
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Dynamicbusiness
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Webfity: Professional website builder tool
- Webfity is a professional website builder tool that allows you to create a high-quality website in minutes.
- Features include hundreds of web design templates, advanced customization options, mobile optimization, SEO optimization, and ecommerce capabilities.
- Webfity offers different pricing plans, including a Free plan, Pro plan, and Business plan.
- Visit webfity.com for more information and to start building your professional website.
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Medium
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Building a Business Plan: A Step-by-Step Guide
- A business plan is the road map to your business, keeping you on course for your goals and informed of challenges.
- The process of creating a business plan involves defining your business, conducting market research, developing marketing and sales strategies, creating a financial plan, outlining the structure of operations and management, and continually reviewing and revising the plan.
- A business plan serves as a living document that needs to be continuously reviewed and updated.
- Following these simple steps can help you have a well-rounded business plan to successfully launch and grow your business.
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Medium
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2024 — The Year of AI; Redefining Product Development at Tatango
- AI is transforming how software development is performed across the entire lifecycle, changing how we build, test and deliver features to customers
- Tools like GitHub Copilot for Business, AI-powered test coverage and LLM-driven release notes are empowering developers to take full ownership of test coverage
- FigJam AI automates clustering ideas, synthesising feedback and drawing actionable insights for user research and design, while Figma AI enhances the ability to focus on creativity and strategy
- AI is automating routine tasks like feedback collection and ticket creation, freeing up product managers to concentrate on higher-value tasks
- AI eliminates manual QA and project management tasks related to testing, enabling developers to take full ownership by writing comprehensive unit and end-to-end (E2E) tests
- AI-driven tools are also enabling us to handle data more efficiently, empowering data engineers with broader development tasks and enabling application developers to handle more advanced data work
- Tools like Circleback automate meeting summaries, improving visibility into team dynamics and ensuring every team member remains aligned and productive
- AI is transforming how Tatango builds, tests and delivers software, accelerating SOC-2 and HIPAA compliance efforts and enabling us to ship features even faster without compromising quality
- As AI-assisted code generation continues to evolve, productivity and quality gains will continue, redefining software development and fundamentally altering how we solve problems, collaborate, and deliver value.
- AI is not just a tool; it's a catalyst for reimagining what is possible and empowering organizations to innovate faster, perform better and lead change.
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Hackernoon
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OpenAI Makes it Easier to Build Your Own AI Agents With API
- OpenAI's Assistance API provides a solution to make it easier for building AI agents for advanced integrations, document retrieval, executing python code for computations, larger context limit, and more. It addresses limitations of chat completion models such as lack of persistent message history, direct handling of large documents, challenging tasks for coding, limited context windows, and synchronous processing. Through OpenAI Assistance API, users can create sophisticated AI assistants featuring tools like code interpreters, function calling, and thread handling.
- Chat completion models like GPT-4o and GPT-4 are simple as they expect a sequence of messages as input. These models are synchronous and expect a single response after the question is asked where in the Assistance API, you can request multiple requests in parallel and combine the results without careful orchestration.
- The Assistance API dynamically selects which message is to be included as context and thus reduces the distance between the previous conversation and current, making it possible for the API to process longer and larger interaction smoothly.
- With the Assistance API, document retrieval involves dividing the text into small chunks, converting them into embeddings, storing them in a vector database, and retrieving the relevant chunks at query time.
- Code interpretation allows the assistant to use Python code in response to requests like reversing a string, finding today's date. The assistant, in turn, does not solely rely on token predictions.
- The OpenAI Assistance API keeps track of message history, supports document retrieval, executes Python code, manages larger contexts and enables function calling for advanced integrations.
- The threaded messaging feature of the Assistance API allows the previous message content to be stored in threads, allowing assistants to keep the conversation context in multiple turns of conversation. Assistance API current supports GPT-4 (1106 preview) and will support custom fine-tuned models in the future.
- The Assistance API offers solutions that address the core limitations of standard chat completions in real-time computation, document-based Q&A, or dynamic interactions in AI applications.
- By using instructions, threads, tools, and function calling, users can create AI assistants that can easily handle everything from reversing string to advanced integrations.
- OpenAI Assistance API brings new possibilities for building sophisticated AI-driven systems for real-world scenarios and making it easier to build AI agents.
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TechCrunch
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Google is using Anthropic’s Claude to improve its Gemini AI
- Contractors working to improve Google's Gemini AI are comparing its answers against outputs produced by Anthropic's competitor model Claude.
- Gemini contractors use the internal Google platform to compare Gemini to other unnamed AI models and have noticed references to Anthropic's Claude.
- Claude's safety settings are stricter than Gemini's and it avoids certain prompts it considers unsafe.
- Google has not disclosed whether it obtained Anthropic's approval to access Claude.
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TechBullion
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Transforming Creativity with the AI Spicy Story Generator
- The AI Spicy Story Generator offered by My Spicy Vanilla is revolutionizing storytelling by combining artificial intelligence with creativity.
- This tool allows users to generate customized and unique stories based on their preferences of genre, tone, characters, and themes.
- The generator excels at crafting engaging narratives with unexpected plot twists and dynamic character arcs.
- It is not only beneficial for professional writers but also serves as an educational tool and provides entertainment for all users.
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Medium
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ZOMATO’s Secret Sauce: Grouping Unique Address Using SBERT
- Zomato used SBERT for text-based clustering of addresses, eliminating the issue of word embedding alone not being able to solve the sequencing of words.
- SBERT allowed for uniformity in processing addresses of varying lengths, resulting in embeddings of a consistent size and meaningful representation of sentences.
- These embeddings of one fixed-length vector can be clustered into one string using DBSCAN, generating one final label for the different addresses of the same location that customers enter.
- SBERT is a type of artificial intelligence model that learns words and their meanings like BERT, but also checks if two sentences mean the same, offering a big idea of what it learned, instead of talking about every single word.
- The Siamese network structure of SBERT, where two identical BERT models share weights, allows for a direct comparison between two input sentences or addresses.
- Encoders in Transformers are used to analyze and encode input sequences into a rich, contextual representation, while decoders generate the output sequence step by step using information from the encoder.
- Transformers process all input tokens simultaneously, making training faster and more efficient than traditional recurrent neural networks.
- Zomato's use of SBERT enabled it to group unique addresses, reducing discrepancies in cost calculations for delivery and the time and resources wasted by delivering to the same address but to different groups of people, which can be harmful for any last-mile delivery aggregator.
- SBERT's fixed-length embeddings offer a meaningful representation of entire sentences, enabling the clustering of addresses of varying lengths with a consistent size.
- Large Language Models, such as Chat-GPT and BERT, are trained on vast amounts of data and used for a wide range of language-related tasks, including understanding and generating human-like text.
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Medium
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Scaling Smarter: An Overview of Large Language Models (LLMs) and Their Compression Techniques Part…
- Part 1 provides an overview of LLMs, discussing their advantages, disadvantages, and use cases.
- Some important LLM models/frameworks/tools with pros, cons, and use cases are listed below. The ones given are GPT-3.5, GPT-4, GPT-2, LLaMA 2, Alpaca, DistilBERT, MiniLM, TinyBERT, BERT, Sentence-BERT, RoBERTa, Faiss (Facebook AI Similarity Search), ONNX Runtime, TensorRT, Hugging Face Transformers, Transformers.js, and ggml.
- Type: Large Transformer-based LLM
- Type: Medium-sized LLM
- Type: LLM
- Type: Fine-tuned LLaMA
- Type: Transformer-based LLM
- Type: Transformer-based LLM
- Type: Transformer-based LLM
- Type: Sentence Embedding Model
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Medium
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The Beauty of ChatGPT Poetry: Strikingly Elegant Yet Missing Two Vital Elements
- AI-generated poetry appears flawless and captivating on the surface but lacks authenticity and personal experience.
- ChatGPT's poetry lacks the ability to feel emotions or appreciate the beauty of life.
- Its creations, though beautiful, lack the passion and personal truths found in human poetry.
- AI-generated poetry can mimic structure, but it falls short in delivering the emotional depth and shared human experience.
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Tech Story
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Intel Announces CES 2025 Keynote: Set to Compete with AMD and NVIDIA
- Intel announces CES 2025 keynote, scheduled for January 6, 2025.
- Intel expected to showcase 14th-Gen Meteor Lake processors, AI-powered solutions, expansion of Arc GPUs, and next-gen data center innovations.
- AMD and NVIDIA also set to deliver keynotes on January 6, showcasing new processors, GPUs, and AI advancements.
- CES 2025 provides Intel an opportunity to battle market challenges, showcase AI innovations, and reinforce brand leadership.
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