IBM Journey to AI blog

DECEMBER 13, 2023

If the ciphertext is intercepted and the encryption algorithm is strong, the ciphertext will be useless to any unauthorized eavesdroppers because they won’t be able to break the code. There are two types of symmetric key algorithms: Block cipher: In a block cipher, the cipher algorithm works on a fixed-size block of data.

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Marktechpost

MAY 18, 2024

Search Algorithms: The system employs search algorithms such as IDA (Iterative Deepening A*) and RBFS (Recursive Best-First Search) to explore the transformation space effectively. Conclusion Data mapping as a search problem provides a novel and effective approach to automating the discovery of mappings between structured data sources.

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Data Integration Machine Learning Algorithm Automation 86

Aiiot Talk

MARCH 20, 2024

This step involves cleaning your data, handling missing values, normalizing or scaling your data and encoding categorical variables into a format your algorithm can understand. It enhances the quality of your data to improve your model’s ability to learn from it. Each piece must fit perfectly to complete the picture.

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Machine Learning Categorization Artificial Intelligence Artificial Intelligence 214

Aiiot Talk

JANUARY 17, 2024

Algorithms generate potential ideas and trends to prepare workforces for public health shifts and increase attentiveness to customers and patients. The packing process outputs clean, defect-free bottles and blister packages because visual algorithms notice missing or broken fragments, color and size abnormalities, or breaks in seals.

Data Integration 147

Data Integration Robotics AI AI 147

Pickl AI

OCTOBER 9, 2023

However, with the emergence of Machine Learning algorithms, the retail industry has seen a revolutionary shift in demand forecasting capabilities. This technology allows computers to learn from historical data, identify patterns, and make data-driven decisions without explicit programming.

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Machine Learning Algorithm ML Data Quality 98

AI News

MAY 20, 2024

Only a third of leaders confirmed that their businesses ensure the data used to train generative AI is diverse and unbiased. Furthermore, only 36% have set ethical guidelines, and 52% have established data privacy and security policies for generative AI applications.

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Unite.AI

MAY 23, 2024

Onboarding data into AI systems is a crucial step that requires careful planning and execution. The goal is to streamline data integration processes to enable AI models to learn effectively from the data.

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AI AI AI Engineer Machine Learning 269

Pickl AI

MAY 30, 2024

You will collect and clean data from multiple sources, ensuring it is suitable for analysis. You will perform Exploratory Data Analysis to uncover patterns and insights hidden within the data. Data Cleaning Data cleaning is crucial for data integrity.

Data Analysis 52

Data Analysis Data Science Data Scientist Data Quality 52

Unite.AI

SEPTEMBER 21, 2023

AI systems can process large amounts of data to learn patterns and relationships and make accurate and realistic predictions that improve over time. Organizations and practitioners build AI models that are specialized algorithms to perform real-world tasks such as image classification, object detection, and natural language processing.

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Marktechpost

MAY 8, 2024

Extensions to the base DQN algorithm, like Double Q Learning and Prioritized replay, enhance its performance, offering promising avenues for autonomous driving applications. DRL models, such as Deep Q-Networks (DQN), estimate optimal action policies by training neural networks to approximate the maximum expected future rewards.

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Deep Learning Neural Network Data Scarcity Natural Language Processing 104

Marktechpost

MAY 15, 2024

Artificial intelligence hinges on using broad datasets, drawing from global internet resources like social media, news outlets, and more, to power algorithms that shape many facets of modern life. The training of generative models, such as GPT-4, Gemini, Cluade, and others, relies on often insufficiently documented and vetted data.

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Metadata AI Developer AI Development Artificial Intelligence 94

IBM Journey to AI blog

OCTOBER 30, 2023

Real-time data analytics helps in quick decision-making, while advanced forecasting algorithms predict product demand across diverse locations. AWS’s scalable infrastructure allows for rapid, large-scale implementation, ensuring agility and data security.

AI 197

AI AI Generative AI Algorithm 197

Unite.AI

SEPTEMBER 22, 2023

Jay Mishra is the Chief Operating Officer (COO) at Astera Software , a rapidly-growing provider of enterprise-ready data solutions. And then I found certain areas in computer science very attractive such as the way algorithms work, advanced algorithms. What initially attracted you to computer science?

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Large Language Models Automation Artificial Intelligence Artificial Intelligence 278

IBM Journey to AI blog

APRIL 15, 2024

Data integration stands as a critical first step in constructing any artificial intelligence (AI) application. While various methods exist for starting this process, organizations accelerate the application development and deployment process through data virtualization. Why choose data virtualization?

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Marktechpost

MARCH 22, 2024

DATALORE uses Large Language Models (LLMs) to reduce semantic ambiguity and manual work as a data transformation synthesis tool. Second, for each provided base table T, the researchers use data discovery algorithms to find possible related candidate tables. This information will then be indexed as part of a data catalog.

Machine Learning 127

Machine Learning Explainability Categorization ETL 127

Heartbeat

OCTOBER 25, 2023

Next-generation sequencing (NGS) platforms have dramatically increased the speed and reduced the cost of DNA sequencing, leading to the generation of vast amounts of genomic data. Integrating and analyzing data from multiple platforms and experiments pose challenges due to data formats, normalization techniques, and data quality differences.

Machine Learning 52

Machine Learning Data Scientist Convolutional Neural Networks Algorithm 52

Pickl AI

OCTOBER 18, 2023

Automatic Data Capture: Streamlining Data Entry with AI AI has the remarkable ability to extract data without manual intervention, allowing employees to focus on more critical tasks, such as customer interactions. AI assists in suggesting what data to acquire from specific sources and establishing connections within the data.

Data Quality 52

Data Quality ML Natural Language Processing Machine Learning 52

AWS Machine Learning Blog

DECEMBER 7, 2023

Amazon Forecast is a fully managed service that uses machine learning (ML) algorithms to deliver highly accurate time series forecasts. Calculating courier requirements The first step is to estimate hourly demand for each warehouse, as explained in the Algorithm selection section.

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Convolutional Neural Networks Algorithm Neural Network Machine Learning 93

IBM Journey to AI blog

SEPTEMBER 6, 2023

Real-time data integration As seen in platforms like IBM Planning Analytics , real-time data integrations ensures that budgets are always up to date. Since data from different sources is instantly merged and processed, delays become a thing of the past.

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Data Integration Artificial Intelligence Artificial Intelligence Algorithm 210

Heartbeat

OCTOBER 23, 2023

The Role of Data Scientists and ML Engineers in Health Informatics At the heart of the Age of Health Informatics are data scientists and ML engineers who play a critical role in harnessing the power of data and developing intelligent algorithms.

Data Scientist 52

Data Scientist Machine Learning Big Data Algorithm 52

Unite.AI

SEPTEMBER 18, 2023

The Paillier algorithm works as depicted. De-Identification De-Identification is a method that is commonly used to anonymize personal identification information of a user in the data by separating the data from the data identifiers, and thus reducing the risk of data tracking.

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Topbots

OCTOBER 4, 2023

Generated with Bing and edited with Photoshop Predictive AI has been driving companies’ ROI for decades through advanced recommendation algorithms, risk assessment models, and fraud detection tools. The predictive AI algorithms can be used to predict a wide range of variables, including continuous variables (e.g.,

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Generative AI Natural Language Processing Machine Learning Convolutional Neural Networks 118

Marktechpost

MAY 12, 2024

Furthermore, Datarails’ AI chatbot FP&A Genius aids forecasting by providing solutions to any queries or scenarios you or management may have, all based on reliable and historical data. Its initial AI algorithm is designed to detect errors in data, calculations, and financial predictions.

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AI Tools Neural Network Artificial Intelligence Artificial Intelligence 83

Pickl AI

MARCH 10, 2023

The following blog will discuss the familiar Data Science challenges professionals face daily. It will focus on the challenges of Data Scientists, which include data cleaning, data integration, model selection, communication and choosing the right tools and techniques.

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Data Scientist Data Science Data Integration Auto-classification 52

IBM Journey to AI blog

JANUARY 10, 2024

Some example use cases to highlight: Confidential AI: leverage trustworthy AI and while ensuring the integrity of the models and confidentiality of data Organizations leveraging AI models often encounter challenges related to the privacy and security of the data used for training and the integrity of the AI models themselves.

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AI Modeling Data Integration Machine Learning LLM 180

Marktechpost

JANUARY 27, 2024

Improving LLM Safety: Data Selection and Bias Mitigation: Training LLMs on carefully curated data sets that are diverse, high-quality, and free from bias can help reduce the spread of misinformation. Techniques like data augmentation and counterfactual training can also help address biases and misinformation present in existing data.

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LLM Large Language Models Prompt Engineer Prompt Engineering 134

Aiiot Talk

SEPTEMBER 13, 2023

Data analysts also require significant computational power. This enables data scientists to run complex algorithms without owning powerful machinery. Additionally, many data science tools and software platforms are now cloud-based. With cloud services, you get on-demand processing capabilities.

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AWS Machine Learning Blog

MAY 15, 2023

Getir used Amazon Forecast , a fully managed service that uses machine learning (ML) algorithms to deliver highly accurate time series forecasts, to increase revenue by four percent and reduce waste cost by 50 percent. Deep/neural network algorithms also perform very well on sparse data set and in cold-start (new item introduction) scenarios.

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Neural Network Convolutional Neural Networks Metadata Data Scientist 66

Unite.AI

OCTOBER 11, 2023

Traditional Databases : Structured Data Storage : Traditional databases, like relational databases, are designed to store structured data. This means data is organized into predefined tables, rows, and columns, ensuring data integrity and consistency.

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Pickl AI

NOVEMBER 23, 2023

We will navigate the landscape of AI’s ascendancy and underscore the pivotal role of integrating AI with robust data protection measures. It is not merely a technological alliance but a strategic imperative for future-proofing security in a world where data integrity and privacy are pillars of trust in the digital realm.

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Artificial Intelligence Artificial Intelligence AI AI 52

ODSC - Open Data Science

MAY 31, 2023

A very common pattern for building machine learning infrastructure is to ingest data via Kafka into a data lake. From there, a machine learning framework like TensorFlow, H2O, or Spark MLlib uses the historical data to train analytic models with algorithms like decision trees, clustering, or neural networks.

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Machine Learning Data Ingestion Neural Network Data Science 131

Towards AI

MAY 8, 2024

Through the integration of Vertex AI with Google Earth Engine, users may gain access to sophisticated machine learning models and algorithms for more efficient analysis of Earth observation data. Enhanced Machine Learning Capabilities: To create, implement, and oversee machine learning models, Vertex AI offers a single platform.

Machine Learning 79

Machine Learning Large Language Models AI Engineer Data Science 79

Pickl AI

AUGUST 31, 2023

Data Profiling refers to the process of analysing and examining data for creating valuable summaries of it. The process of data profiling helps in understanding the structure, content and interrelationships of data. It supports metadata analysis, data lineage, and data quality assessment.

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ETL Data Quality Data Integration Metadata 52

Heartbeat

JANUARY 3, 2024

Can algorithms, neural networks, and data analytics offer tangible solutions to mitigate the climate crisis? ML can sift through this data deluge by leveraging advanced algorithms and computational methodologies, uncovering hidden patterns, correlations, and insights that may elude human analysis.

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Machine Learning ML Algorithm ESG 52

Heartbeat

SEPTEMBER 20, 2023

This technology has broad applications, including aiding individuals with visual impairments, improving image search algorithms, and integrating optical recognition with advanced language generation to enhance human-machine interactions. Various algorithms are employed in image captioning, including: 1.

Natural Language Processing 52

Natural Language Processing Computer Vision NLP Algorithm 52

IBM Journey to AI blog

JANUARY 29, 2024

Another is augmented reality technology that uses algorithms to mimic digital information and understand a physical environment. Intelligent, data integration platform example: State Bank of India State Bank of India (SBI) saw its customer base grow their wealth and found they were looking for new opportunities.

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Automation Artificial Intelligence Artificial Intelligence Big Data 169

AWS Machine Learning Blog

DECEMBER 4, 2023

His focus was building machine learning algorithms to simulate nervous network anomalies. He joined Getir in 2019 and currently works as a Senior Data Science & Analytics Manager. His team is responsible for designing, implementing, and maintaining end-to-end machine learning algorithms and data-driven solutions for Getir.

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BERT Auto-complete Data Scientist Machine Learning 89