A naukri.com initiative
Data Science News
Medium
1M
181
Image Credit: Medium
The Future of AI/ML & Data Science: Opportunities, Trends, and Challenges
- AI is transforming business operations through automation and data-driven decision-making.
- Generative AI is being used in creative fields to produce content.
- AI is enhancing code development and improving real-time performance through edge computing.
- Challenges include the need for explainable AI, ensuring data quality, addressing bias, and overcoming the talent shortage.
Read Full Article
10 Likes
Analyticsindiamag
1M
158
Image Credit: Analyticsindiamag
The Breakthrough AI Scaling Desperately Needed
- Researchers from Google, Max Planck Institute, and Peking University introduced a new approach called TokenFormer that addresses scaling issues faced by traditional transformer architecture.
- TokenFormer introduces a token-parameter attention (Pattention) layer that enables incremental scaling without full retraining of the entire model from scratch.
- This approach has demonstrated impressive results, successfully scaling from 124M to 1.4B parameters while maintaining performance comparable to Transformers trained from scratch.
- TokenFormer’s most compelling features is its ability to preserve existing knowledge while scaling, offering a new approach to continuous learning.
- In benchmark tests, TokenFormer achieved performance comparable to standard Transformers, requiring only one-tenth of the computational budget.
- This efficiency extends to both language and vision tasks, with the model demonstrating competitive performance across various benchmarks, including zero-shot evaluations and image classification tasks.
- Furthermore, TokenFormer maintains constant computational costs for token-token interactions while scaling parameters, thus making it suitable for processing longer sequences.
- However, users from Hacker News have pointed out some issues, saying it is hard to trust the numbers shown in the research.
- TokenFormer provides a new level of modularity and compatibility between publicly available weight sets, assuming they use similar channel dimensions.
- While the approach looks promising on paper, we'll have to wait for developers to implement it in actual models.
Read Full Article
9 Likes
Analyticsindiamag
1M
90
Image Credit: Analyticsindiamag
Tata Communications is Building Self-Reliant and Sovereign AI Cloud in India
- Tata Communications is preparing to launch its AI Cloud services to train, deploy, and inference AI models for India’s enterprises, startups, and government.
- It seeks to offer a complete stack of solutions that address the entire AI lifecycle, including the often-overlooked inferencing stage.
- Tata Communications’ partnership with NVIDIA enables them to provide optimal GPU capabilities to power AI models.
- The AI Cloud also offers multilingual models to reflect the diverse linguistic landscape of India’s local market.
- The company aims to help establish India as an AI Super Factory and be the top partner in such initiatives.
- Tata Communications offers a full-stack approach that allows customers to build their own AI Super Factories.
- It has introduced AI Studio, a platform that simplifies the model development process and optimizes each step.
- The AI Studio provides access to a wide range of models such as Mistral and Llama 2 for flexibility and experimentation.
- Tata Communications has emphasised the importance of responsible AI practices and built-in guardrails to ensure reliable AI outcomes.
- The AI Cloud offers a comprehensive data management system that allows collecting, curating, and governing data from anywhere, including hybrid deployments.
Read Full Article
5 Likes
Analyticsindiamag
1M
313
Image Credit: Analyticsindiamag
Snowflake Partners with Anthropic to Deliver AI Solutions for Enterprises
- Snowflake and Anthropic have announced a multi-year strategic partnership to deliver AI capabilities to global enterprises.
- Anthropic’s Claude 3.5 Sonnet model will be integrated into Snowflake Cortex AI on AWS, enabling secure, scalable AI-driven workflows, conversational assistants, and generative analytics.
- The collaboration combines Claude’s reasoning with Snowflake’s data governance, powering AI products like Snowflake Intelligence and Cortex Analyst for secure enterprise use.
- Anthropic's Claude 3.5 Sonnet will initially launch in select AWS regions through Amazon Bedrock, offering enterprises enhanced reasoning, conversational capabilities, and secure deployment.
Read Full Article
18 Likes
Medium
1M
90
Image Credit: Medium
Data Scientists and Python — A Practical Implementation
- Python serves as the foundation for implementing data science skills like mathematics, communication, and machine learning.
- The article provides a practical example of using Python for exploratory data analysis.
- The dataset used in the example has a balanced distribution, and certain features show interesting correlations.
- The article suggests various strategies for retention and customer segmentation based on the analysis.
Read Full Article
5 Likes
Analyticsindiamag
1M
90
Image Credit: Analyticsindiamag
How AI Chips Stole the Spotlight in 2024
- Big tech companies like NVIDIA and AMD make special chips that power everything from driverless cars to smart gadgets.
- Indian company, Vicharak recently secured funding of ₹1 crore, for creating Vaaman, a compact computing board featuring a six-core ARM CPU and a field-programmable gate array (FPGA) with 1,12,128 logic cells.
- In the race to power AI applications, inference chips are the unsung heroes driving real-time decisions, from chatbots to recommendation engines.
- NVIDIA rolled out its highly anticipated H200 Tensor Core GPU, a successor to the H100, designed for generative AI and high-performance computing workloads.
- Google’s parent company Alphabet released two notable AI chips, including the Cloud TPU v5p.
- AWS has switched its focus from cloud infrastructure to chips.
- In a bid to keep pace with the growing demand for semiconductors capable of training and deploying large AI models, Intel announced its latest AI chip Gaudi 3
- Cerebras Systems announced the development of Condor Galaxy 3 (CG-3), the latest addition to their AI supercomputing constellation, in 2024.
- After the success of the M1 chip, Apple released the M4 chip, but it is only available in iPad Pro.
- IBM unveiled the Spyre Accelerator at the Hot Chips 2024 conference.
Read Full Article
5 Likes
Medium
1M
186
Image Credit: Medium
Understanding Generalization, Underfitting, and Overfitting in k-Nearest Neighbors (kNN)
- Generalization is the model’s ability to apply what it has learned during training to new data.
- Underfitting occurs when the model is too simplistic to capture the underlying patterns in the data.
- Overfitting happens when the model learns not only the underlying patterns but also the noise in the training data.
- The key to good generalization in kNN is finding the optimal value of k that balances bias and variance.
Read Full Article
11 Likes
Medium
1M
254
Image Credit: Medium
Python Decorators: The Superpower Capes of Your Functions
- Decorators in Python enhance functions with new abilities
- Decorators add extra steps before and after running the main code
- Decorators can handle arguments, work with functions that take inputs and return outputs, and stack together
- Real-world applications of decorators include web frameworks, resource access management, and caching
Read Full Article
15 Likes
Analyticsindiamag
1M
123
Image Credit: Analyticsindiamag
WTF is Nikhil Kamath Doing with Young Entrepreneurs?
- Zerodha co-founder Nikhil Kamath unveiled the ‘Innovators under 25’ initiative, marking the launch of WTFund
- WTFund, a non-equity fund, selected 15 entrepreneurs providing up to INR 20 lakh in non-equity grants
- The entrepreneurs can retain the full ownership of their startup with Kamath not having any stake in them
- Kamath is empowering resilient founders who deeply understand their problem space
- Mars Computers aims to make high-performance computing accessible via the cloud, designed to disrupt the creative and developer ecosystem
- BioCompute uses DNA storage for archival storage with cost-effective and sustainable storage solutions
- RNT Health Insights improves early detection of gastric cancer using AI with spatial and temporal deep learning models
- Pixa build AI-powered toys that function as personalised tutors for children aged 5 to 12
- CallPrep transforms sales workflows by automating pre-meeting preparation, giving sales reps accurate insights
- WTFund also invested in Urban Animal, Oh! Nuts, Pawsible Foods and Pamawel which offer sustainable and healthy solutions for humans and pets
Read Full Article
7 Likes
Medium
1M
163
Image Credit: Medium
A City of Dreams: A Tale of Islamabad
- Aisha, a young architect in Islamabad, has dreams as expansive as the hills that surround her city.
- She is inspired by the fusion of modernity with nature and the harmonization of culture with progress in the city.
- Aisha often weaves her heritage into her work, blending Pakistan's rich Mughal architecture with contemporary styles.
- Beyond her professional aspirations, Aisha also dreams of bringing about change and addressing the disparities in Islamabad's government and society.
Read Full Article
9 Likes
Dev
1M
354
Image Credit: Dev
1072. Flip Columns For Maximum Number of Equal Rows
- Given an m x n binary matrix, we are to determine the maximum number of rows that have all values equal after some number of column flips.
- We can solve this problem by calculating the pattern and the complementary pattern for each row.
- Using a hash map, we can count the occurrences of patterns and their complements.
- The maximum count for any single pattern or its complement gives the result.
Read Full Article
21 Likes
Hackernoon
1M
159
Image Credit: Hackernoon
Mastering Scraped Data Management (AI Tips Inside)
- The article explores the automatic data processing and export of scraped data from web pages. Web Scrapers need to process the raw data for export so your team or company can actually extract value from it. Most popular methods for both manual and automatic data processing like using custom regular expressions and automatic data processing with AI. AI-based tools (LLMs) are revolutionizing data processing. The article covers ways to collect raw data via web scraping and then pass it to AI for data cleaning. Classic methods for storing scraped data like CSV, JSON, or XML format and most effective methods for exporting data with specialized formats like Protobuf, Parquet, AVRO, and ORC were discussed. Exporting data to online SQL or NoSQL databases and cloud storage providers like AWS S3 or Google Cloud Storage were also included. The article also covers webhooks and how webhooks send data directly to external services in real-time. Lastly, the article explores how top-tier data providers like Bright Data process and handle scraped info. Compliance with GDPR and CCPA for scraped data were also discussed.
Read Full Article
9 Likes
Mit
1M
49
Image Credit: Mit
Advancing urban tree monitoring with AI-powered digital twins
- MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), Google, and Purdue University have developed a new system named “Tree-D Fusion” that accommodates the merging of Artificial Intelligence (AI) and tree-growth models. It produces accurate 3D models of existing urban trees and environmental data that can help predict how individual trees will grow over time and impact their surroundings.
- Tree-D Fusion produces the first-ever large-scale database of 600,000 environmentally aware simulation-ready tree models across North America, using Google Street View and deep learning.
- The model predicts how trees would grow under different environmental conditions and climate scenarios, such as different possible local temperatures and varying access to groundwater. Policymakers can use this for proactive planning by anticipating where growing branches might tangle with power lines or strategically placing trees to keep neighborhoods cool.
- AI-based tree modeling helps in environmental justice by mapping urban tree canopy in unprecedented detail and uncovering disparities in green space access across different socioeconomic areas. The team is working with ecologists and tree health experts to refine these models so that benefits branch out to all residents equitably.
- Their digital modeling system captures the intricate dance of shade patterns throughout the seasons, revealing how strategic urban forestry could hopefully evolve sweltering city blocks into more naturally cooled neighborhoods.
- Tree-D fusion is exciting because it pushes researchers to rethink fundamental assumptions in computer vision, where even a gentle breeze can dramatically alter tree structures from moment to moment.
- The dataset is a springboard for future innovations in computer vision, and they’re already exploring applications beyond street view imagery and to platforms like iNaturalist and wildlife camera traps. The goal is to extend the platform’s capabilities to a planetary scale.
- The research is supported by the United States Department of Agriculture’s (USDA) Natural Resources Conservation Service and the National Institute of Food and Agriculture.
- The researchers presented their findings at the European Conference on Computer Vision in August.
Read Full Article
3 Likes
VentureBeat
1M
399
Google Cloud launches AI Agent Space amid rising competition
- Google Cloud launches AI Agent Space, a new ecosystem program.
- AI Agent Space enables businesses to discover, deploy, and co-create AI agents.
- The initiative positions Google as a major player in the AI agent space.
- Currently, the AI Agent Space offers a limited number of agent models.
Read Full Article
24 Likes
Medium
1M
172
Image Credit: Medium
Revving Up Insights: Predicting Car Prices with Regression Models and Model Interpretability
- The dataset consists of 405,002 rows and 12 columns.
- Data processing techniques were implemented to improve the quality of the dataset.
- A number of features were engineered or simplified to improve the model's interpretability.
- The feature space was reduced using principal component analysis (PCA) and Scikit Learn selection to improve model performance and interpretability.
- Four models were considered: Linear Regression, Random Forest Model, Gradient Boosting Regressor, and Averager/Voting Regressor.
- The performance of each model was compared; the Voting Regressor was found to be the most suitable for this application.
- The SHAP (SHapley Additive exPlanation) algorithm was used to provide global and local explanations of the models.
- The feature importance analysis was executed for each model.
- The model-predicted values were plotted against the actual values for each model.
- The results show that the model is capable of providing accurate car prices within seconds.
Read Full Article
10 Likes
For uninterrupted reading, download the app