#AIForGood

[mezzopieno-news]

Tecnologia e sostenibilità si incontrano sotto il mare

🌊✨ La tecnologia che ama il mare. GhostNetZero, un sonar intelligente, sta trovando e rimuovendo le reti fantasma dagli oceani di tutto il mondo. Oltre 26 tonnellate di reti pericolose già eliminate! 🐬 Innovazione e amore per la natura, insieme. 💙

[shopcontroller]

Don't let another customer slip away. Get started NOW with your 7-day FREE trial of VoiceController AI and experience the future of auto shop customer engagement! 🔗 https://shop-controller.com/voicecontroller

The first 24/7 AI Phone Agent built for auto repair, collision, and towing businesses! VoiceController answers the phone, asks your customer's critical questions, and schedules appointments right to your calendar, around the clock. Give it a listen!

[thedevmaster-tdm]

You Won't Believe How Easy It Is to Implement Ethical AI

[bloggerkeke]

How is AI transforming every aspect of human life?

AI is transforming every aspect of human life by revolutionizing the way we work, communicate, learn, and live. Here are some key areas where AI is making a significant impact:

What is Artificial Intelligence?

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that can perform tasks requiring human-like cognitive abilities. It involves machine learning, natural language processing, computer vision, and other advanced techniques.

How does it impact every industry?

AI has the potential to revolutionize every industry by automating processes, analyzing vast amounts of data, and making intelligent predictions. It improves efficiency, enhances decision-making, and drives innovation across sectors such as healthcare, finance, manufacturing, and transportation.

How does it impact every individual?

AI impacts individuals by providing personalized experiences, virtual assistants, and smart devices. It enhances daily life through voice recognition, recommendation systems, and virtual customer support. AI-powered technologies make our lives easier, more convenient, and efficient.

AI is transforming every aspect of human life by revolutionizing the way we work, communicate, learn, and live. Here are some key areas where AI is making a significant impact:

1. Healthcare: 

AI is enhancing medical diagnosis, drug discovery, and personalized treatment plans. It helps analyze vast amounts of patient data, identify patterns, and provide accurate predictions for disease prevention and early intervention.

According to Accenture, AI in healthcare could potentially save up to $150 billion annually for the U.S. healthcare economy by 2026.

The global AI in healthcare market is projected to reach $45.2 billion by 2026, growing at a compound annual growth rate (CAGR) of 44.9% from 2019 to 2026.

2. Education: 

AI is revolutionizing education by enabling personalized learning experiences, adaptive tutoring, and intelligent assessment systems. It helps tailor educational content to individual student needs, track progress, and provide timely feedback for better learning outcomes.

The global AI in education market is expected to reach $3.68 billion by 2025, with a CAGR of 38.17% from 2018 to 2025.

A study by the American Institutes for Research found that AI-powered tutoring systems have a positive impact on student learning outcomes, resulting in an average percentile gain of 28 points.

3. Transportation: 

AI is driving advancements in autonomous vehicles, optimizing traffic management systems, and improving transportation efficiency and safety. It enables self-driving cars, real-time navigation, and predictive maintenance, revolutionizing the way we commute and travel.

The global autonomous vehicle market is projected to reach $556.67 billion by 2026, with a CAGR of 39.47% from 2019 to 2026.

According to the National Highway Traffic Safety Administration, AI-powered advanced driver-assistance systems (ADAS) have the potential to reduce traffic fatalities by up to 94%.

4. Communication: 

AI-powered language translation, natural language processing, and speech recognition technologies are transforming communication. Chatbots, virtual assistants, and language translation tools facilitate seamless cross-cultural communication and enhance accessibility.

The global AI in communication market is expected to reach $3.5 billion by 2026, growing at a CAGR of 34.7% from 2019 to 2026.

AI-powered language translation technologies have advanced significantly, with Google Translate handling more than 100 billion words daily in over 100 languages.

Virtual assistants like Siri, Alexa, and Google Assistant leverage AI to understand and respond to user commands, making voice-based communication more convenient and efficient.

5. Entertainment: 

AI is reshaping the entertainment industry with personalized content recommendations, virtual reality experiences, and computer-generated imagery. It enhances user experiences, facilitates content curation, and enables immersive storytelling.

The global AI in the entertainment market is projected to reach $5.5 billion by 2026, with a CAGR of 25.4% from 2019 to 2026.

AI algorithms are used in content recommendation systems of streaming platforms like Netflix and Spotify, which account for a significant portion of their user engagement and revenue.

AI-powered computer-generated imagery (CGI) has transformed the visual effects industry, enabling the creation of realistic and immersive experiences in movies, video games, and virtual reality.

6. Finance: 

AI is revolutionizing the financial industry with automated trading, fraud detection, risk assessment, and personalized financial advice. It enables efficient data analysis, real-time market insights, and improved decision-making processes.

A report by PwC estimates that AI could contribute up to $15.7 trillion to the global economy by 2030, with the financial sector being one of the largest beneficiaries.

AI-driven automated investment platforms, also known as robo-advisors, managed over $1 trillion in assets globally in 2020.

7. Smart Homes: 

AI-powered smart home devices and virtual assistants, such as voice-activated speakers and smart thermostats, make our daily lives more convenient and efficient. They automate tasks, provide personalized recommendations, and create a connected and intelligent living environment.

The global smart home market is expected to reach $246.97 billion by 2027, with a CAGR of 11.6% from 2020 to 2027.

Voice-activated smart speakers, powered by AI assistants like Amazon Alexa and Google Assistant, have seen widespread adoption. As of 2021, there were over 200 million smart speakers in use worldwide.

8. Manufacturing: 

AI-driven robotics and automation technologies optimize manufacturing processes, increase productivity, and improve product quality. AI-enabled machines and robots perform complex tasks, enhance precision, and enable predictive maintenance.

The global AI in manufacturing market is expected to reach $16.7 billion by 2026, growing at a CAGR of 49.5% from 2019 to 2026.

According to Deloitte, companies that invest in AI and advanced automation technologies in manufacturing can experience productivity gains of up to 30%.

AI-powered predictive maintenance can reduce equipment downtime by up to 50% and maintenance costs by up to 10-40%.

9. Agriculture: 

AI is transforming agriculture by optimizing crop management, monitoring soil conditions, and predicting weather patterns. It enables precision farming techniques, reduces resource waste, and improves agricultural productivity.

The global AI in agriculture market is projected to reach $4 billion by 2026, with a CAGR of 22.5% from 2021 to 2026.

AI-powered agricultural robots and drones are expected to reach a market value of $1.3 billion by 2026.

The use of AI in agriculture can increase crop yields by up to 70%, according to a study by the International Data Corporation (IDC).

10. Cybersecurity: 

AI is strengthening cybersecurity measures by detecting and preventing cyber threats, identifying anomalous behavior, and improving data protection. AI algorithms analyze large datasets to detect patterns and anomalies, enhancing security measures.

According to Gartner, by 2022, 90% of security budgets will be allocated to addressing AI-powered cyber threats.

The global AI in cybersecurity market is projected to reach $38.2 billion by 2026, growing at a CAGR of 23.3% from 2021 to 2026.

In summary: 

AI is transforming every aspect of human life, from healthcare and education to transportation, communication, entertainment, finance, and beyond. Its applications are vast and diverse, revolutionizing industries, improving efficiency, and enhancing the overall human experience. As AI continues to advance, it holds immense potential to shape a future where intelligent technologies seamlessly integrate into our daily lives, making them more convenient, productive, and enriching.

[harshitaly]

The Rise of Artificial Intelligence 🤖💡

Discover how AI is shaping society, ethics, and advancements in our latest blog post! Dive deep into the fascinating impact of this cutting-edge technology and join the conversation.

🌍 Dive into the ethical considerations surrounding AI. Learn how we can ensure fairness, transparency, and accountability in algorithmic decision-making systems. Join us in shaping an AI-powered future that benefits all.

[aiexpressway]

What Do Robots Think? Find Out In The World's First Robot Conference!

[techaivisionx]

AI Predicting Natural Disasters: How Technology is Saving Lives!

What if we could know about an earthquake, flood, or wildfire before it even happens? This video dives into amazing new ways AI is predicting natural disasters and how this artificial intelligence technology is saving lives around the world.

From Japan getting early earthquake warnings to Canada fighting wildfire alerts with AI, and NASA using powerful AI systems with satellites – we're getting days, not just hours, of warning! Learn how AI watches seismic patterns, weather fronts, and real-time sensor data to give us critical information and rescue people.

But how accurate are these predictions? And what big challenges are still out there to make this a worldwide solution? Join us to see how AI predicting natural disasters is changing how we prepare for nature's powerful forces. We'll show you real-life examples and look at exciting future tech like quantum computing and AI-on-orbit satellites. You'll discover why AI disaster prediction might be our best friend in the fight for survival.

This isn't science fiction anymore – it's happening now! See how AI is revolutionizing disaster preparedness and making us safer. Don't miss this eye-opening look at the future of saving lives with technology.

What do you think? Could AI be our strongest ally against the next big disaster?

[wisepl]

Precision Annotations for Every Aircraft

Airplanes aren’t just flying objects - they’re data points in motion.

We transform raw aerial and satellite imagery into structured intelligence with high-precision airplane detection annotation. Whether it’s for defense analytics, aviation mapping, or geospatial AI - our annotations fuel the accuracy your model needs to soar.

From runway parking to mid-air flight paths, we label it all:

Bounding Boxes

Segmentation Masks

Object Tracking

Altitude & Pose Estimation (custom tagging)

Your model deserves more than automation - it deserves insight.

Let’s power your vision with pixel-perfect precision. DM us or email info@wisepl.com to get a free sample annotation trial. Collaborate with a human-in-the-loop annotation team that gets aerospace.

[printlyst]

Artificial Intelligence (AI) is revolutionizing the technological future by driving automation, enhancing healthcare, and transforming industries. While it promises unprecedented efficiency and innovation, it also raises ethical, economic, and societal challenges. The key lies in responsible development to harness AI's potential while mitigating risks

Donate Us: paypal.me/teldawi

[mezzopieno-news]

Innovazione medica e IA per salvare vite

Una piccola provetta per una grande svolta. Un test domestico, basato sull’intelligenza artificiale, può individuare il tumore alla prostata prima ancora che si manifesti. Dimentica biopsie invasive e diagnosi tardive. Il futuro della medicina è già qui, e ci entra in casa in punta di piedi.

[leadwithaipodcast]

🎯 600,000 races. 🎯 600,000 races. 📊 40% prediction accuracy — and climbing toward 70%. 🏇 AndVegas it’s not  doing the betting. 🧠 That’s right. In the next episode of Lead with AI, I sit down with Mike Skura, fintech founder and creator of RaceOracle AI — the machine learning engine built to disrupt horse racing with predictive precision. This isn’t about gambling. It’s about how AI is changing an industry that hasn’t changed in a century. 🎧 Episode drops June 17. 🔗 Subscribe now: https://www.youtube.com/@LeadWithAiPodcast #LeadWithAI #MikeSkura #RaceOracleAI #SportsTech #AIinAction #PredictiveAI #SmartBetting #MachineLearning #DigitalDisruption #FutureOfSports #TechThatWins https://www.youtube.com/watch?v=Fr5ObhhHVmE via Tamara Nall https://www.youtube.com/channel/UCXeTZTxyDfstd-pieJH0WQg June 12, 2025 at 03:29PM

[humanbe]

WHAT A PLEASURE TO SEE YOU ALL AGAIN ON THIS FIRST DAY!! Don’t forget to get your ticket for @VivaTech the world’s rendezvous for #STARTUPS & #LEADERS TO CELEBRATE THE #FUTURE on June 11-14 in @Paris More at 👉 http://vivatechnology.com @LesEchos @PublicisGroupe #VivaTech #LetsBreakTheCycle #TechForGood #AIforGood #NoPlanetB #theFutureIsNOW #StartupForGood #VivaTechnology #ClimateAction #Change #WorldLeaders #Paris #humanbe #WeAreOne

[jacelynsia]

Is Your Smartwatch Smarter Than Your Doctor? How AI in Wearables Is Shaping the Future of Preventive Health

AI-powered wearables are no longer just fitness trackers—they’re becoming essential tools for early disease detection and preventive care. But how reliable are real-time insights? And what does this mean for healthcare providers, insurers, and patients alike? Dive into the transformative role of AI in wearable health tech, where constant monitoring meets proactive care.

[impact-newswire]

Hamburg Declaration on Responsible Artificial Intelligence (AI) for the Sustainable Development Goals (SDGs)

Why We Take Action We are at a crossroads. Despite the progress made in recent years, we need renewed commitment and engagement to advance toward and achieve the Sustainable Development Goals (SDGs). Digital technologies, such as Artificial Intelligence (AI), can play a significant role in this regard. AI presents opportunities and risks in a world of rapid social, political, economic,…

[segmed]

What if your medical data could help save lives worldwide? Hospitals generate massive amounts of imaging data, yet more than 80% of it remains unused for research. Imagine the breakthroughs we’re missing! AI in healthcare is only as good as the data it learns from—so how can we do better? At Segmed, we’re dedicated to unlocking the full potential of Real-World Imaging Data (RWiD) to drive innovation in healthcare. By providing structured, de-identified radiology images and reports from diverse populations, we empower researchers to: ✅ Train AI models faster and more accurately ✅ Develop better medical devices with real-world data ✅ Improve patient outcomes through precision medicine ✅ Strengthen clinical trials with real-world evidence

[nschool]

Data Science and Artficial Intelligence Key concepts and Application

Introduction

In the modern world with constantly developing technology Data Science vs Artificial Intelligence are becoming more and more interrelated. While Data Science is concerned with mining data So AI takes it a step higher by building machines with the ability to learn, reason and even decide. The integration of these two disciplines is revolutionalising various industries throughout the world by bringing in optimised systems and strategies. As Data Science plays the role of creating the proper input by putting together clean and organized data, AI extends it by creating smart models that learn. Combined, they comprise the generation that embraces the future of innovation and development for countless opportunities in almost every industry.

What is Data Science?

Data Science is a multi-disciplinary field, which deals with the processing of data into meaningful information. It combines some methods from statistics, machine learning, as well as data engineering to work with data, make conclusions, and provide decision support. Some of the most used are python, R and SQL which assist in cleaning, processing and even visualization of data. 

What is Artificial Intelligence?

Artificial Intelligence (AI) on the other hand is the reproduction of human intelligence methodologies by computer systems. It basically implies the ability of a machine to imitate functions that are normally associated with human cognition for instance, speech recognition, decision making and problem solving among others. Machine learning is one of the main branches of AI; others are natural language processing and computer vision that lie behind voice assistants and self-driving cars.

Fundamental Concepts of Data science and Artificial Intelligence

Core Differences Between Data Science and AI: Although Data Science and AI are related, they are two different fields although share some similarities. Data Science is about discovering information from data with the help of statistics, AI is about building machines that act like humans. Data Science mostly involves exploration, discovery and analysis of patterns and trends in data while AI also emulates decision-making in addition to analysis. AI also relies on models that are self-tuning and can become better with time unlike the conventional data analysis techniques. 

Overlap Between Data Science and AI: The most apparent intersection of Data Science and AI is machine learning (ML). This is because ML models which are the key components of AI work using data which is gathered, purified and formatted by Data Scientists. Due to this, data science is associated with AI where the quality of data determines the success of the

Key Components of Data Science and Artificial Intelligence

Data Science Components: 

 Data Collection: The first step that is involved in this process is collection of raw data from sources such as databases, internet APIs or surveys.

Data Cleaning and Processing: This includes error correction, management of missing values, and data format transformation for further analysis. 

Statistical Analysis and Visualization: Data Scientists employ statistical techniques to analyze the data and employ graphical interfaces such as Mat plot lib or Power BI to portray the results in a comprehendible manner. 

 Data Modeling and Interpretation: The last process is the modeling process which include creating models such as predictive models to yield information and make decisions. 

 AI Components: 

Machine Learning Algorithms: They include supervised learning algorithms such as classification, regression learning algorithms, unsupervised learning algorithms including clustering and dimensionality reduction learning algorithms as well as reinforcement learning algorithms. 

Natural Language Processing (NLP): NLP is an important component that helps AI systems understand and produce human language needed in functions such as voice recognition or translation. 

 Computer Vision: Image processing is a way that AI decode the visual information which may help in the implementation of features such as face identification, objects’ detection/ recognition, and radiography. 

Robotics and Automation: Robots are capable of executing operations with the help of AI to make them operate independently whether in factories or usage in hospitals and several other houses.

 Data Science: Applications and Use Cases 

Business Intelligence and Analytics: Data Science helps make decisions as it gives business insights derived from data analytics. Banks and other companies incorporate predictive analytics into their business models to be able to predict market trends, manage the most effective ways of marketing as well as categorize customers. They are currently using big data analysis to understand the patterns of consumer behavior such that businesses can create innovative products and services. 

Healthcare: It is also widely used in the field of healthcare where patient data analysis is paramount in the treatment processes through the formulation of individualized treatment plans. It also helps in medical research where it reviews clinical data, identifies the compatibility of drugs as well as ability to forecast diseases using epidemiology data. 

Finance: Banks, making efficient use of various data types, use data science, for example, to detect credit card fraud, to assess credit risk for loans, and for algorithmic trading. Machine learning, with an ability of learning from previous data formerly processed, can predict a given transaction as fraudulent and, therefore, limit financial fraud. Besides, they create models that they use to predict the market and hence help in investment decisions.

E-commerce: E-commerce organizations leverage data science to develop customized shopping experiences based on user behavior. Such techniques allow developing valuable insights about demand and supply and applying them to inventory management. 

Artificial Intelligence: Uses of applications and specific examples

Autonomous Vehicles: Self-driving automobiles employ AI in processing data coming from the different sensors, cameras and radar systems to compute environment. AI assist in real-time decisions making including identifying of barriers, pedestrian movements and traffic unpredictable scenes.

Healthcare: For example, some of the industries that AI is disrupting includes medical imaging, diagnostics, and even patient personalized treatment. The AI technologies help the doctors to identify the irregularities in the X-rays and the MRIs, diagnose diseases at the initial stage, and prescribe the right medications according to the patient’s genes.

Retail and Customer Service: AI helps the customers through the artificial intelligence in the form of chatbots and virtual assistances which respond to the customer queries and suggestions, ordering processes etc. The customer profiling systems used by AI-enabled applications based on the customer’s penchant to prescribe products that suit their tastes.

Manufacturing and Robotics: In the process of manufacturing, AI is applied in facilitating production processes to minimize the use of human resource and time wastage. AI is also used in the predictive maintenance whereby it studies data from the equipment to forecast when it will fail and when it should be taken for maintenance.

Data Science vs Artificial Intelligence

Focus and Objectives:

Data Science is mostly about analysis and deeper interpretation of the essence of a problem about data. It aims to utilize data for decision-making purposes.

AI is centered on designing machines that can smartly execute tasks including the ability to decide, learn, and solve problems.

Skill Sets:

For a Data Scientist, fundamental competencies are data management, data analysis, and programming knowledge of SQL, Python, and R but for an AI professional their competencies are in algorithm implementation, different machine learning approaches, and implementation of AI using toolkits such as Tensor flow and Pytorch among others.

Tools and Technologies:

Data Science: They include  pandas, numpy, R, and Matplotlib for data manipulation and visualization.

AI: Accessible tools that are employed for the training and development of machine learning models include TensorFlow, Scikit-learn, and Keras.

Workflows and Methodologies:

Data Science: It involves analyzing and processing data by following key steps such as data collection, cleaning, inspection, visualization, and analysis to extract meaningful insights and inform decision-making.

AI: Typically, it encompasses model construction, model training, model validation, and model deployment with a data set of big data and compute power for deep learning.

The Convergence of Data Science and AI

How Data Science Enables AI: Data Science is the most important part and the base of all AI projects because AI profoundly relies on clean structured data for training the models. To be more precise, data scientists clean up and engineer large amounts of data to be ready for learning by artificial intelligence. This means that if data science is not well done within an organization then the ability of AI models to perform will be affected by poor quality data.

AI Enhancing Data Science: AI is simplifying many challenges in Data Science by applying it in various areas and being a tool in data preprocessing through cleaning data, feature selection, and other applications like anomaly detection. With the help of AI tools data scientists can manage and accomplish tasks more quickly and discover insights at a higher pace.

Future Trends in Data Science and AI

Integration of AI in Data Science Workflows: AI is being integrated into the Data Science process as a crucial enabler which is evident by the increasing use of AutoML systems that are capable of selecting the model, training as well and tuning it.

Evolving AI Applications: SI is transitioning from single-skill oriented to multiskilled machines, thus giving a more generalized system that will require much less human interaction. Others includeData privacy, bias, and accountability issues are emerging as ethical issues in the development of AI.

New Opportunities for Collaboration: This is because the two areas of Data Science and AI will continue to develop with increased integration across multiple disciplines. The teams will include data scientists, artificial intelligence engineers, and specific subject matter domain experts who will come together to work on intricate challenges and build intelligent solutions for sectors such as healthcare, finance, and education.

Conclusion

Even though Data Science and AI have to do with data and data processing, their objectives and approaches are not the same. Data Science is the process of drawing inferences or making decisions with the help of data and AI is about creating autonomous entities which can learn on their own. The future of both fields is however interrelated in the sense that an AI system will depend on the kind of data processed by data scientists. Data Science and AI require competent workers or specialists who are equipped with efficient knowledge in those industries. The demand for professionals in Data science and AI will rise as various companies across their kind embark on gainful research through advanced technology.