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# AI / ML 90
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Ukrainian Oncology Conference
SciForce at UpToDate 5.0: Insights from Ukrainian Oncology Conference

The SciForce Medical team recently attended a major oncology conference in Ukraine. The two-day event in Kyiv brought together over 2,000 experts, including doctors, researchers, and industry leaders. It provided a great chance to learn about the latest advancements in cancer care and connect with potential partners. The conference had a busy schedule of sessions, workshops, and presentations on topics like cancer diagnostics,advanced treatments, and personalized care. Since we couldn’t attend

Published: December 23, 2024
# Healthcare
# AI / ML
# Big Data
# Data Science
Synthetic Data
Synthetic Data: A Passing Trend or the Future of AI?

What if businesses could access unlimited, high-quality data without privacy risks or tedious preparation? Synthetic data for AI model training is making this possible, offering a scalable, efficient alternative to real-world data. Gartner predicts synthetic data will surpass real data in AI model training by 2030, with the market growing from $351.2 million in 2023 to USD 2,339.8 million by 2030, at a CAGR of 31.1%. Data preparation is a major hurdle, with data scientists spending over 60% of t

Published: December 9, 2024
# AI / ML
# Big Data
# Data Science
# LLM
Step-by-Step Guide
Step-by-Step Guide to Creating Your Own Large Language Model

LLMs are enabling computers to understand and generate human-like text, making them indispensable in industries ranging from customer service to content creation. The global market for LLMs is expected to skyrocket from $1.59 billion%20market%20size%20in%20terms%20of,79.80%25%20during%202024%2D2030.) in 2023 to $259.8 billion by 2030, with North America alone projected to hit $105.545 million by 2030. The dominance of the top five LLM developers, who currently hold 88.22% of the market revenue,

Published: September 4, 2024
# AI / ML
# Big Data
# Data Science
# LLM
MLOps as The Key to Efficient AI Model
MLOps as The Key to Efficient AI Model Deployment and Maximum ROI

Ever wonder why so many machine learning (ML) models never see the light of day? Despite their huge potential, only 32% of data scientists say their models usually get deployed. Even more shocking, 43% report that 80% or more of their models never make it into production. This means many businesses miss out on the full value of their AI projects. Imagine a retail company spending months developing a sophisticated customer recommendation system, only for it to never be implemented — losing out on

Published: August 7, 2024
# AI / ML
# Data Science
# LLM
Healthcare Data
Turning Chaos into Clarity: Mastering Unstructured Healthcare Data with AI

Healthcare providers manage an enormous volume of data daily, approximately 137 terabytes, most of which is unstructured. This includes a wide array of formats such as medical images, clinical notes, and genetic test results. Unstructured data processing, crucial for patient care, poses significant challenges due to its complexity and the varied sizes of its components. The volume of healthcare data is rapidly increasing, fueled by the widespread adoption of electronic health records and advance

Published: July 17, 2024
# Healthcare
# AI / ML
# Data Science
# LLM
Role of Predictive Analytics cover
From Insights to Action: The Role of Predictive Analytics in Business Transformation

Predictive analytics uses historical data and techniques like statistical modeling and machine learning to drive predictive analytics for business transformation by forecasting future outcomes. It provides accurate forecasts, helping organizations predict trends and behaviors from milliseconds to years ahead. The global predictive analytics market growth was valued at 14.71 billion U.S. dollars in 2023 and is projected to grow from 18.02 billion U.S. dollars in 2024 to 95.30 billion U.S. dolla

Published: June 12, 2024
# FinTech
# Healthcare
# Retail / E-commerce
# Marketing
# Manufacturing
# AI / ML
# Big Data
Top Computer Vision Opportunities
Top Computer Vision Opportunities and Challenges for 2024

Computer vision (CV) is a part of artificial intelligence that enables computers to analyze and understand visual information, both images and videos. It goes beyond plain “seeing” an image, but teaches computers to make decisions based on what they see. The AI-driven computer vision market is experiencing rapid growth, rising from $22 billion in 2023 to an expected $50 billion by 2030, with a 21.4% CAGR from 2024 to 2030. This technology imitates human vision but works faster using sophisticat

Published: March 8, 2024
# Tech
# AI / ML
# Computer Vision
AI Revolution in EdTech
AI Revolution in EdTech: AI in Education Trends and Successful Cases

The usage of Artificial Intelligence in the world of Education Technologies is totally changing the learning approach, offering truly innovative solutions that transform the experience of students and teachers. AI-based solutions are bringing the education industry to a new level by enhancing the learning experience, making it more personalized, interactive, and efficient. Through the last few years, AI has started gaining popularity in many fields, and the EdTech industry is not an exception: a

Published: September 12, 2023
# EdTech / LMS
How to Build Reliable AgTech AI When Farm Data Is Incomplete
How to Build Reliable AgTech AI When Farm Data Is Incomplete

In agriculture, missing data is part of the job. Farm data comes from different sources, under changing field conditions, and at different points in the growing cycle, so a complete and perfectly synchronized dataset is rare. AgTech models still have to work with whatever information is available. Some gaps barely affect the result, while others remove an important part of the signal. Knowing the difference is what makes the model useful outside a clean development dataset. Agricultural data is

Published: September 24, 2026
# Agriculture
# AI / ML
# Data Science
Building Domain-Specific LLM Systems
Building Domain-Specific LLM Systems: When to Use RAG, Fine-Tuning, or Neither

When an Air Canada customer asked the airline’s website chatbot about bereavement fares, it told him he could book first and claim the discount within 90 days. The same answer linked to a policy page saying retroactive requests weren’t allowed. The passenger followed the chatbot’s instructions and later had his refund request rejected. The civil tribunal found the airline liable for negligent misrepresentation after concluding that he’d reasonably relied on the inaccurate guidance. The correct i

Published: September 18, 2026
# AI / ML
# Data Science
# LLM
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