Iguazio

NOVEMBER 16, 2023

This helps enhance collaboration between data scientists and developers, bridge technological silos, and ensure efficiency when building and deploying ML models, which brings more ML models to production faster. Data Privacy and Compliance - Building your own platform can offer more control over data handling and compliance needs.

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Pickl AI

MAY 7, 2023

Data, analytics, AI, and robotics, today, the tech discussions revolve around these topics. One of them is the large volume of data that we are creating every day. But deploying conventional methods to extract insight from this data is not feasible. Here comes the role of Big Data. How Does Facebook Use This Data?

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Pickl AI

OCTOBER 10, 2023

In this blog, we are going to unfold the two key aspects of data management that is Data Observability and Data Quality. Data is the lifeblood of the digital age. Today, every organization tries to explore the significant aspects of data and its applications. What is Data Observability and its Significance?

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The MLOps Blog

FEBRUARY 5, 2023

What comes into your mind when you hear Streaming Data? May be data generated through video streaming platforms like YouTube, but this is not the only thing which qualifies as streaming data. There are many platforms and sources that generate this kind of data. What is streaming data?

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DagsHub

FEBRUARY 29, 2024

Introduction Machine learning models learn patterns from data and leverage the learning, captured in the model weights, to make predictions on new, unseen data. Data, is therefore, essential to the quality and performance of machine learning models. In this blog, I will describe how to prepare data for machine learning in depth.

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Alation

OCTOBER 5, 2021

What is data governance and how do you measure success? Data governance is a system for answering core questions about data. It begins with establishing key parameters: What is data, who can use it, how can they use it, and why? Why is your data governance strategy failing? Common data governance challenges.

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AWS Machine Learning Blog

SEPTEMBER 1, 2023

Specifically, we briefly introduce MLOps principles and focus on the main differentiators compared to FMOps and LLMOps regarding processes, people, model selection and evaluation, data privacy, and model deployment. These data owners are focused on providing access to their data to multiple business units or teams.

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Heartbeat

JANUARY 3, 2024

Can algorithms, neural networks, and data analytics offer tangible solutions to mitigate the climate crisis? Photo by NOAA on Unsplash Data-Driven Insights: Climate science thrives on vast, intricate, and often overwhelming data. sort_values(ascending=False)) # Visualization: Sunlight Hours vs.

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IBM Journey to AI blog

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? One challenge in applying data science is to identify pertinent business issues.

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AWS Machine Learning Blog

NOVEMBER 22, 2023

The AWS Well-Architected Framework provides a systematic way for organizations to learn operational and architectural best practices for designing and operating reliable, secure, efficient, cost-effective, and sustainable workloads in the cloud. This means the system lacks visibility into logs and failures.

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Google Research AI blog

JULY 11, 2023

Nonetheless, computer architecture research is evolving, with industry and academia turning towards machine learning (ML) optimization to meet stringent domain-specific requirements, such as ML for computer architecture , ML for TinyML acceleration , DNN accelerator datapath , memory controllers , power consumption , security , and privacy.

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The MLOps Blog

MARCH 15, 2023

Collaboration : Ensuring that all teams involved in the project, including data scientists, engineers, and operations teams, are working together effectively. Security : Implementing security measures such as access control. This is a blog post from AWS to optimize cloud services costs. S3 buckets.

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Heartbeat

JANUARY 9, 2024

These LLMs are artificial intelligence (AI) systems trained using large data sets, including text and code. This is brought on by various developments, such as the availability of data, the creation of more potent computer resources, and the development of machine learning algorithms.

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Pickl AI

JULY 17, 2023

In this blog, we will take you through some of the biggest revolutions in the generative AI domain and discuss its applications. One of the unique features of generative AI is that it can autonomously generate outputs based on patterns and examples from existing data. What is Generative AI? Top 7 Generative AI Use Cases: 1.

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IBM Journey to AI blog

APRIL 4, 2024

The popularity of private cloud is growing, primarily driven by the need for greater data security. Across industries like education, retail and government, organizations are choosing private cloud settings to conduct business use cases involving workloads with sensitive information and to comply with data privacy and compliance needs.

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Pickl AI

AUGUST 24, 2023

These innovative approaches have revolutionised the process we manage data. This blog highlights a comparative analysis of Edge Computing vs. Cloud Computing. It is the practice of storing and accessing data and applications over the internet. This minimizes the risk of data loss and downtime.

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Dataconomy

JUNE 22, 2023

The development of robust, efficient, and privacy-aware AI language models has long been an area of intense focus. Unlike any other language model, FreedomGPT prioritizes speed, privacy, and offline usage in addition to cutting-edge technology’s many features. For another, your data will be safe with FreedomGPT.

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Mlearning.ai

DECEMBER 21, 2023

Concerns around copyright, privacy, security, ability to do mathematical calculations etc. LLMs are trained on massive amount of data. The data that LLMs are trained on is therefore historical (or dated).e.g. In essence, it meant creating a ChatGPT on proprietary data. It is generally considered an offline process.

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AWS Machine Learning Blog

MAY 7, 2024

We match the most relevant videos to text-based search queries by incorporating new multimodal embedding models like Amazon Titan Multimodal Embeddings to encode all visual, visual-meta, and transcription data. When the job is complete, you can obtain the raw transcript data using GetTranscriptionJob.

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Hacker News

FEBRUARY 24, 2024

in the EU will be broken apps and lost data, affecting schools, governments, startups, gamers, and anyone else with the temerity to look outside the one true app store for even a second. This was all wrapped in a peevish, belligerant presentation, which the good folks over at The Platform Law Blog have covered in depth. What's At Risk?

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Iguazio

FEBRUARY 8, 2024

Data engineers, data scientists and other data professional leaders have been racing to implement gen AI into their engineering efforts. This blog post delves into the concepts of LLMOps and MLOps, explaining how and when to use each one. Continuous monitoring of resources, data, and metrics. What is LLMOps?

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IBM Journey to AI blog

MARCH 28, 2024

As cloud computing continues to transform the enterprise workplace, private cloud infrastructure is evolving in lockstep, helping organizations in industries like healthcare, government and finance customize control over their data to meet compliance, privacy, security and other business needs. billion by 2033, up from USD 92.64

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Ocean Protocol

SEPTEMBER 12, 2023

How to Earn - As a predictoor , trader , or data farmer - From earning to thriving ; early benchmarks 5. Architecture - Privacy & Oasis Sapphire - I mplementation ; backend details 6. Ocean Predictoor is an on-chain, privacy-enabled, AI-powered application and stack that is bringing this dream to reality. Possible Futures 7.

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AWS Machine Learning Blog

JANUARY 17, 2024

Geospatial data is data about specific locations on the earth’s surface. Analysis of geospatial data is sought after in a few industries. It involves understanding where the data exists from a spatial perspective and why it exists there. There are two types of geospatial data: vector data and raster data.

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Heartbeat

MAY 29, 2023

LLMs are trained on massive amounts of text data, allowing them to generate highly accurate predictions and responses. We will also examine the challenges associated with LLMs, such as bias, privacy concerns, and ethical considerations. LLMs rely on vast amounts of text data to learn patterns and generate coherent text.

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IBM Journey to AI blog

DECEMBER 1, 2023

Private cloud combines many benefits of cloud computing with the security and control of on-premises IT infrastructure. Hybrid cloud vs. multicloud Hybrid cloud is frequently confused with multicloud , which refers to using cloud services from more than one cloud vendor.

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IBM Journey to AI blog

FEBRUARY 6, 2024

This infrastructure model relies on a network of remote data centers , servers and storage systems owned and operated by a third-party service provider. A CMP creates a single pane of glass (SPOG) that provides enterprise-wide visibility into multiple sources of information and data.

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AWS Machine Learning Blog

MARCH 14, 2024

However, adoption of these FMs involves addressing some key challenges, including quality output, data privacy, security, integration with organization data, cost, and skills to deliver. Organizations must also carefully manage data privacy and security risks that arise from processing proprietary data with FMs.

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AWS Machine Learning Blog

AUGUST 22, 2023

Machine learning (ML) is revolutionizing solutions across industries and driving new forms of insights and intelligence from data. Many ML algorithms train over large datasets, generalizing patterns it finds in the data and inferring results from those patterns as new unseen records are processed. What is federated learning?

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AWS Machine Learning Blog

JANUARY 4, 2024

One such area that is evolving is using natural language processing (NLP) to unlock new opportunities for accessing data through intuitive SQL queries. Instead of dealing with complex technical code, business users and data analysts can ask questions related to data and insights in plain language.

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phData

MARCH 11, 2024

This blog was co-written by Alex Roed, Luke Kline, Sam Hall, Alec Haase, and Christian Franklin. The depreciation of third-party cookies has only compounded this problem, leaving companies scrambling to figure out how to implement the systems needed to power growth with their first-party customer data. What is a Customer Data Platform?

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AWS Machine Learning Blog

MARCH 4, 2024

The new service achieved a 4-6 times improvement in topic assertion by tightly clustering on several dozen key topics vs. hundreds of noisy NLP keywords. These qualitative data points deepen researchers’ understanding beyond what multiple-choice questions can capture alone.

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IBM Journey to AI blog

JULY 10, 2023

Trust and power are distributed across service providers and application or content creators, consumer privacy is honored (as responsibility of data management moves to the edge) and creators are compensated for their creations. This stifles innovation, and single control points raise risks to application security and user privacy.

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Alation

DECEMBER 14, 2021

They were once typically deployed in traditional data center environments but have been retrofitted and remarketed as “cloud” products. So how do cloud-native vs. cloud-enabled solutions compare? Cloud-native vs. cloud-enabled (and other ‘cloudy’ terms). Cloud-enabled solutions are technologies adapted for the cloud.

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Pickl AI

JULY 23, 2023

Summary: In the modern digital landscape, data analytics has emerged as a powerful tool for businesses and industries seeking valuable insights to drive decision-making and improve performance. Today, it is imperative for companies to adopt the data driven decision making processes. What is Data?

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The MLOps Blog

APRIL 5, 2023

These teams may include but are not limited to data scientists, software developers, machine learning engineers, and DevOps engineers. Additionally, transfer learning can reduce the training data required for the new model, which can be beneficial in situations where training data is scarce.

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Alation

AUGUST 5, 2021

What is Data Quality? Data quality is defined as: the degree to which data meets a company’s expectations of accuracy, validity, completeness, and consistency. By tracking data quality , a business can pinpoint potential issues harming quality, and ensure that shared data is fit to be used for a given purpose.

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