Dr Victoria Holt: life, the universe and everything
Chaos, complexity, curiosity and database systems. A place where research meets industry
Welcome
"The important thing is not to stop questioning. Curiosity has its own reason for existing" Einstein
Friday 8 March 2024
Data Toboggan Slide Preparation: Ask The Fabric Experts at SQLBits
International Womens Day 2024
International Women’s Day 2024, celebrates women’s achievements, progress, and equality. The official campaign theme for International Women’s Day 2024 is 'Inspire Inclusion'. When we inspire others to understand and value women’s inclusion, we create a better world.
Historical Roots
The first International Women’s Day (IWD) was held in March 1911.
IWD transcends borders, organizations, and groups—it’s a day of collective global activism.
World-renowned feminist Gloria Steinem once emphasized that the struggle for equality belongs to all who care about human rights.
Investing in Women: Accelerating Progress
The overarching theme for 2024 is 'Invest in women: Accelerate progress'. It underscores the importance of creating an inclusive society and empowering women. IWD celebrates the social, economic, cultural, and political achievements of women.
The idea of IWD traces back to the 1908 labour movement in New York. Women garment workers marched, demanding better pay, shorter working hours, and voting rights. The movement was spearheaded by the Socialist Party of America.
Just a few of the remarkable women who have made significant contributions to science and technology:
Ada Lovelace
Born in 1815, she was the world’s first computer programmer. Collaborated with Charles Babbage on the Analytical Engine, creating the first algorithm intended for implementation on this early mechanical computer.
Grace Hopper
She was a trailblazing computer scientist who invented the compiler. Her work led to the development of the high-level programming language COBOL, which revolutionized software development and paved the way for modern programming languages.
A 21-year-old aerospace major at MIT. Working on building a powerful rocket for NASA. Inspiring others with her determination and vision.
Marie Curie
Pioneered research in radioactivity. The first woman to win the Nobel Prize (jointly with her husband) in 1903.
Elizabeth Blackwell
First woman to graduate from medical school in the US. She founded a medical school for women in England.
Dr. Mae C. Jemison
First African American woman in space. She holds degrees in chemical engineering and medicine. She served as a Peace Corps medical officer.
Caroline Herschel
Caroline Lucretia Herschel born in 1750 was a German-born British astronomer, whose most significant contributions to astronomy were the discoveries of several comets, including the periodic comet 35P/Herschel–Rigollet, which bears her name
Williamina Fleming
Cracked the secrets of the universe with computation.
Worked at the Harvard College Observatory in the late 1800s. These women have left an indelible mark on science and technology, inspiring generations to come.
Friday 1 March 2024
Mirroring in Microsoft Fabric
Mirroring in Fabric was announced in November as coming soon. When i first heard the term I immediately thought of the deprecated SQL Server Database mirroring term. However the summary from Ignite shared on the MSSQLTips site
There are a few capabilities announced so far
Real-Time Data Replication
No complex setup or ETL processes. Data is replicated reliably and in real-time.
An initial snapshot captures the data, followed by continuous synchronization with every transaction (inserts, updates, deletes).
Mirroring uses Change Data Capture (CDC) technology, transforming it into appropriate Delta tables and landing it in OneLake.
Intelligent logic ensures efficient replication without unnecessary compute usage.
Access and Management
Any database can be accessed and managed centrally within Fabric.
By providing connection details, your database becomes instantly available as a Mirrored database.
Familiar database editors allow seamless management.
Data Warehousing Simplified
Each Mirrored database includes default data warehousing experiences via a SQL Analytics Endpoint.
Whether a SQL developer or a citizen developer, querying is easy using the T-SQL editor with full Intellisense or the visual query editor.
What's next
Initially the article proposes Azure Cosmos DB, Azure SQL DB and Snowflake will be able to use mirroring. You can read more here.
Wednesday 21 February 2024
EU AI Act, the first extensive AI regulation globally, is approved
The European Union (EU) has been working on a new legal framework that aims to regulate the development and use of artificial intelligence (AI) in the EU. The proposed legislation, the Artificial Intelligence (AI) Act, focuses on ensuring that AI systems are trustworthy, respect human values and rights, and support the EU single market.
The AI Act introduces a risk-based approach to classify AI
systems into four categories: unacceptable, high-risk, limited-risk, and
minimal-risk. Unacceptable AI systems are those that pose a clear threat to the
safety, livelihoods, or rights of people, such as social scoring or mass
surveillance. High-risk AI systems are those that are used in critical sectors,
such as healthcare, education, or law enforcement, and have a significant
impact on people’s lives, such as medical devices, recruitment tools, or facial
recognition. Limited-risk AI systems are those that pose some risks to people’s
rights or expectations, such as chatbots, online advertising, or deepfakes1.
Minimal-risk AI systems are those that pose no or negligible risks to people,
such as video games, spam filters, or smart appliances.
The AI Act imposes different obligations and requirements
for each category of AI systems. Unacceptable AI systems are banned from being
developed, sold, or used in the EU. High-risk AI systems must comply with
strict rules on data quality, transparency, human oversight, accuracy,
security, and accountability. They must also undergo a conformity assessment
before being placed on the market or put into service. Limited-risk AI systems
must provide clear and adequate information to users about their nature,
purpose, and capabilities. Minimal-risk AI systems are subject to voluntary
codes of conduct and best practices.
The AI Act also establishes a governance structure and a
cooperation mechanism for the implementation and enforcement of the rules. The
European Commission will be responsible for monitoring and updating the list of
high-risk AI systems and sectors, as well as adopting delegated and
implementing acts. The European AI Board will be an independent advisory body
that will provide guidance and recommendations to the Commission and the member
states. The national competent authorities will be in charge of supervising and
sanctioning the compliance of AI systems with the rules, as well as ensuring
cross-border cooperation.
The AI Act is a landmark proposal that aims to make the EU a
global leader in trustworthy and human-centric AI. However, it also faces some
challenges and criticisms from various stakeholders, such as industry, civil
society, and other countries. The AI Act will need to balance the interests and
concerns of different actors, as well as adapt to the fast-changing and
evolving nature of AI
There is a pyramid of risk.
References
https://www.weforum.org/agenda/2023/06/european-union-ai-act-explained/
https://www.bbc.com/news/world-europe-67668469
Thursday 15 February 2024
Fundamentals of Generative AI
Generative AI is a branch of artificial intelligence that focuses on creating new content or data from scratch, such as images, text, music, or code. Generative AI models learn from existing data and use it to generate novel and realistic outputs that are not part of the original data. Some of the applications of generative AI include:
Image synthesis: Generative AI can create realistic images of faces, landscapes, animals, or objects that do not exist in the real world.
Text generation: Generative AI can produce natural language texts on various topics, such as stories, poems, essays, or code.
Music composition: Generative AI can compose original music in different genres, styles, and moods.
Data augmentation: Generative AI can enhance or expand existing data sets by creating new samples that are similar but not identical to the original ones. This can help improve the performance and robustness of machine learning models. For example, generative AI can create new images of handwritten digits or new sentences of natural language.
The main challenge of generative AI is to ensure that the generated outputs are both diverse and realistic, meaning that they cover a wide range of possibilities and resemble the real data. To achieve this, generative AI models often use two types of techniques:
Probabilistic models: These are models that learn the probability distribution of the data and sample from it to generate new outputs. For example, variational autoencoders (VAEs) are probabilistic models that encode the data into a latent space and decode it back into the original space, adding some noise in the process to create variations.
Adversarial models: These are models that consist of two components: a generator and a discriminator. The generator tries to create outputs that fool the discriminator, while the discriminator tries to distinguish between real and fake outputs. The two components compete with each other and improve over time. For example, generative adversarial networks (GANs) are adversarial models that use neural networks as the generator and the discriminator.
Generative AI is a fascinating and rapidly evolving field of artificial intelligence that has many potential benefits and applications for society. However, it also poses some ethical and social risks, such as misuse, deception, or bias. Therefore, it is important to develop and use generative AI models responsibly and transparently, with respect for human values and rights.
To learn more about the Fundamental of Generative AI , Microsoft Learn has a great course
It also covers what is the Azure OpenAI service. This being a Microsoft's cloud solution for deploying, customizing, and hosting large language models. There is a brief overview of CoPilot.
Thursday 1 February 2024
Data Toboggan - Purview in Microsoft Fabric
Excited to be speaking at Data Toboggan
Event Date: 3rd February 2024
Register now for free: https://bit.ly/DT24-Register
Agenda: https://bit.ly/DT24-Agenda
Abstract
Microsoft Fabric comes with Purview for data governance. What does that mean and how can it help with managing your data estate. This session looks to connect the dots between the old and new and explains, which of the apps exist in Fabric.
Data Toboggan Winter Edition 2024
Please join us on Saturday for the #DataToboggan winter edition. We have 32 speakers, 3 tracks, including an AI track. Lots of fun and learning. We also have the amazing Knee-deep in Tech not to be missed and a keynote from Kim Manis
Event Date: Saturday 3rd February 2024
Register now for free: https://bit.ly/DT24-Register
Agenda: https://bit.ly/DT24-Agenda