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Dev
1h
153
Image Credit: Dev
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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Dynamicbusiness
1h
92
Image Credit: Dynamicbusiness
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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TechCrunch
2h
110
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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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Medium
2h
42
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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
1h
212
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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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TechCrunch
1h
243
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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
1h
171
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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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Medium
1h
299
Image Credit: Medium
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
1h
285
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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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TechBullion
2h
231
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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
2h
258
Image Credit: Medium
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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15 Likes
Medium
2h
188
Image Credit: Medium
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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11 Likes
Tech Story
2h
320
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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Dev
2h
208
Image Credit: Dev
Async Pipeline Haystack Streaming over FastAPI Endpoint
- This tutorial explains how to use Server-Sent Events (SSE) in a Python-based pipeline and how to serve the processed query results over an endpoint using FastAPI with an asynchronous, non-blocking solution.
- The post describes a workaraound approach to create a pipeline task and set "sync" streaming callbacks on the event loop for chunk collection and yield the chunks in a server-sent event.
- The pipeline is designed synchronously, and components to the pipeline can be added dynamically. The API KEY is passed through the end-point, and the openai generator is used to create a pipeline component, which is used to generate responses for user input.
- The AsyncPipeline is defined to run the pipeline, and the server-sent event is used to stream the generated answers in SSE format.
- The ChunkCollector is defined to handle and queue the generated answers and yield them in SSE formatting in an end-point.
- The end-point can be served using fetch-event-source as a frontend to display the streams of generated answers.
- The post concludes by suggesting that the use of sockets would be useful considering performance issues while handling a large volume of data.
- The packages required for the tutorial include fastapi, uvicorn, haystack-ai, haystak-experimental, pydantic, and python, above version 3.10 and below 3.13.
- The complete code, snippets, and a full explanation for each function are provided above.
- The tutorial is meant for experts who are familiar with FastAPI and python programming languages, as it does not provide a guide for the FastAPI process.
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Medium
2h
195
What Goes Beyond the Prompt?
- Tokenization provides structure for the AI to process the input.
- Transformers use self-attention to handle different cases.
- Transformers process words in parallel, enabling faster computations and improved context analysis.
- The Transformer architecture consists of two main parts.
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