A naukri.com initiative
Deep Learning News
Medium
1w
385
Image Credit: Medium
Mayo Clinic Pioneers AI in Mental Health
- Mayo Clinic is leading the way in integrating Artificial Intelligence (AI) in mental health care.
- The scarcity of mental health professionals is a global concern, and AI is helping to fill the gaps.
- Mayo Clinic's research aims to refine accessibility and precision in mental health services.
- By combining technology and empathy, Mayo Clinic is transforming how mental health conditions are perceived and treated.
Read Full Article
23 Likes
Medium
2w
72
Image Credit: Medium
Discover the Future of AI Search with Perplexity
- Perplexity AI is integrating advanced language models and introducing new features to enhance search capabilities.
- Perplexity AI aims to provide personalized, efficient, and effective search solutions.
- The combination of models like GPT-4 Turbo, GPT-4o, and Claude 3 enhances AI search capabilities.
- Perplexity AI strives to create a seamless conversation-like experience for users.
Read Full Article
4 Likes
Medium
2w
270
Image Credit: Medium
PrivaSEE: The ML Architecture Transforming Privacy Policy Understanding
- PrivaSEE is a new app that allows users to get privacy recommendations on other apps simply by uploading their terms & conditions agreements.
- The app is split into three components: source control and data prep, machine learning and user interaction.
- The machine learning components include a fine-tuned model to help identify and classify privacy issues within the annotated text data of the ToS;DR website.
- The app lets users upload a PDF of a service’s terms and conditions and receive a list of identified privacy attributes with a weighted score adjusted by severity and importance by category.
- Users can also ask for app recommendations, which filters results based on a variety of criteria and uses a weighted ranking system to find the top rated app.
- The API and front-end for the app have been implemented using React, Javascript and a FastAPI to create the backend RESTful APIs that handle frontend communication
- Deployment was automated on a GCP host using Ansible and Kubernetes were used to handle scalability.
- The team would like to expand their app to support other types of agreements and reach a larger audience.
Read Full Article
16 Likes
Medium
2w
257
Image Credit: Medium
The Unstoppable Rise of Zero-Shot Learning in 2025
- Zero-Shot Learning is revolutionizing machine learning in 2025 by predicting the unpredictable and harnessing unseen data.
- Zero-Shot Learning (ZSL) is a breakthrough solution that bridges the gaps in understanding without relying on manually labeled datasets.
- ZSL offers a shortcut in unsupervised learning, allowing for exploration of uncharted territories without getting lost.
- ZSL is transforming the field of machine learning by enabling innovative strides in unsupervised learning.
Read Full Article
15 Likes
Medium
2w
107
Summary of Course Large Language Model Agents by Prof Dawn Song an Team
- The course on Large Language Model (LLM) Agents covered various topics and frameworks.
- Week 2 focused on LLM Agents, which are systems that use large language models to interpret instructions, perform tasks, and interact with their environment.
- Week 3 discussed Agentic AI frameworks and Multimodal LLMs. Agentic AI frameworks like Autogen and Langchain enable AI systems to perform tasks on behalf of humans. Multimodal LLMs improve the collaboration and communication between multiple LLM agents.
- Week 4 explored the enterprise trends for generative AI, including the use of LLM for user search data and the importance of finetuning and efficient models.
Read Full Article
6 Likes
Medium
2w
339
Image Credit: Medium
Deep Learning Frameworks for Image Recognition
- Deep learning frameworks are key for image recognition
- The author describes their fascination with witnessing machines interpret images
- Convolutional Neural Networks (CNNs) are the building blocks of image recognition
- Deep learning frameworks play a crucial role in enabling machines to 'see'
Read Full Article
20 Likes
Medium
2w
176
AI incorporation into the internet business
- AI recommendation engines boost conversion rates in e-commerce by analyzing user behavior and providing personalized recommendations.
- AI optimizes digital marketing by analyzing data and delivering targeted ads, resulting in higher ROI.
- AI manages inventories by predicting demand patterns and keeping optimal stock levels.
- While AI integration brings advantages, it also poses challenges such as data privacy and initial investment.
Read Full Article
10 Likes
Medium
2w
396
Image Credit: Medium
Quantum Futures: Unveiling the Power of Computing Beyond Limits
- The potential of quantum computing is to revolutionize sectors like cryptography, AI, and drug discovery.
- Quantum computing could transform drug discovery by allowing researchers to simulate complex biochemical reactions at a speed and scale that classical computers cannot match.
- Quantum computing is poised to enhance artificial intelligence by handling vast amounts of data at unprecedented speeds, significantly improving decision-making processes.
- Quantum computing holds the promise to be a game-changer in medicine, AI, and various other fields.
Read Full Article
23 Likes
Medium
2w
202
Nanotechnology Nano refers to nanotechnology as being about the manipulation and engineering of…
- Nanotechnology has been rooted in the conceptual thought processes of Richard Feynman, who proposed the manipulation of individual atoms and molecules as being the fundamental building blocks of matter controlled at the atomic level.
- The practical foundation of the modern iteration of nanotechnology was established with the invention of tools that allow scientists to observe and manipulate atoms. These tools include the scanning tunneling microscope (STM).
- In the 1990s, carbon nanotubes were discovered and became one of the most studied materials under nanotechnology, showcasing exceptional properties by way of mechanics, electricity and thermal conduction.
- Throughout the 2000s, numerous advancements emerged, such as the discovery of graphene bringing an exceptional degree of strength and conductivity to the industry. Additionally, this era saw an increase in the commercialisation and practical application of nanotechnology.
- The maturation of nanotechnology has brought forth concerns regarding ethics, the environment and health implications. However, this era has seen the creation of guidelines to ensure responsible and safe development of nanotechnology.
- Nanotechnology continues to revolutionize a multitude of industries worldwide, with far-reaching possibilities to solve some of humanity's greatest challenges, offering solutions in areas such as healthcare, energy, and environmental sustainability.
- Nanobots and molecular machines represent the potential to create intricate products atom by atom, although challenges such as ethical issues, scalability of the production process, and achieving safety standards remain.
- The future of nanotechnology holds promise of creating smarter, more sustainable, and efficient systems in various sectors including the possibility of revolutionizing cancer treatment, drug delivery, and diagnostics.
- The technology is rapidly evolving, with the possibility to play an even more central role in shaping the future of science, engineering, and society.
- Further developments are needed to ensure that the progress in nanotechnology is guided by ethical principles and responsible practice to help create a sustainable future.
Read Full Article
12 Likes
Medium
2w
21
Image Credit: Medium
Measuring the Minds of Machines: A Journey Through AI Benchmarks
- AI benchmarks play a crucial role in measuring progress in the field of artificial intelligence and understanding different languages and cultures.
- These benchmarks allow researchers to evaluate and compare the performance of AI models, identifying strengths and weaknesses.
- AI benchmarks are diverse, covering areas such as general language understanding, code generation, specific domains, and multilingual capabilities.
- Evaluating Multilingual General Semantic Understanding involves assessing direct translation as well as other linguistic complexities.
Read Full Article
1 Like
Hackernoon
2w
164
Image Credit: Hackernoon
Synthetic Data in Face Recognition: A Game Changer or Just Hype?
- Large-scale datasets are essential for training effective face recognition (FR) systems, but acquiring real-world data presents numerous challenges like ethical and privacy concerns.
- Synthetic data is a potential solution to overcome these challenges, but it is not yet a substitute for real-world datasets.
- Synthetic datasets can be more cost-effective, easier to obtain, and do not raise issues like consent for use, privacy compliance, and bias. They also allow for the creation of controlled environments for testing and tuning FR models.
- However, synthetic datasets lack the diversity and complexity of real-world datasets and fail to capture all the variations present in real data, resulting in worse model performance.
- Synthetic data holds promise for advancing FR technology, but it is essential to recognize its current limitations. The quality of synthetic face data is catching up to real-world data, with data generation techniques improving, but it may still be a while before synthetic data eliminates the need for real-world face data for FR training.
Read Full Article
9 Likes
Medium
2w
104
Image Credit: Medium
Aviation and Artificial Intelligence: A Partnership for a Smarter Future
- AI plays a crucial role in air traffic management, optimizing flight flows and reducing delays.
- Predictive maintenance using AI helps prevent potential failures and improves safety.
- AI enhances airport security by analyzing passenger data and surveillance systems.
- AI-powered smart assistants and robots improve the passenger experience from booking to in-flight services.
Read Full Article
6 Likes
Medium
2w
334
Image Credit: Medium
LLMs: The Wall Is Now a Mirror
- Gary Marcus questions the industry's fixation on LLMs as a panacea for AI advancement.
- The misalignment between AI hype and reality may undermine the broader field of AI.
- The next leap in AI may require a fundamental rethinking of intelligence.
- The industry needs to look beyond LLMs and explore interdisciplinary approaches.
Read Full Article
20 Likes
Medium
2w
426
Image Credit: Medium
The Non-Triviality of Enforcing Precise Output Length Constraints in LLMs
- Enforcing precise output length constraints in large language models (LLMs) is non-trivial.
- Existing models learn a distribution that reflects natural language statistics rather than structural constraints.
- Attempts to impose minimum or exact lengths involve formulating constrained optimization problems using Lagrange multipliers.
- Alternative methods like reinforcement learning and heuristic approaches have limitations and do not guarantee exact length control.
Read Full Article
25 Likes
Medium
2w
382
Image Credit: Medium
Causality in AI and Counterfactual Reasoning
- Judea Pearl’s causal calculus provides a formal framework for reasoning about causality.
- The key operator is do(⋅), representing external intervention.
- Structural equation modeling (SEM) is a cornerstone of counterfactual reasoning.
- Counterfactuals are hypothetical scenarios: “What would Y have been if X were different?”
- Causal inference underpins critical applications in AI.
- Counterfactual reasoning provides a principled approach to ensuring fairness, enhancing explainability, and optimizing decisions in dynamic systems.
- Causal inference in AI faces several theoretical and computational challenges.
- One exciting frontier is counterfactual generative adversarial networks (CGANs).
- Causality also has profound implications for scientific discovery.
- There are several Python libraries designed for basic causal inference tasks.
Read Full Article
23 Likes
For uninterrupted reading, download the app