#Research Data Security

[leonbasinwriter]

AI-Driven Cybersecurity: Protecting Education from Breaches

By Leon Basin | Alumnus, Santa Clara University Leavey School of Business | Bridging Academic Rigor & Real-World Cybersecurity Executive Summary 2025 Education Cyberattack Snapshot In 2025, 56% of U.S. school districts suffered cyber breaches—many stemming from compromised privileged accounts (K12 SIX). With K-12 breach costs averaging $4.45M per incident (IBM), institutions must act…

[cosmosjourney1]

🏥 AI in Healthcare: How Artificial Intelligence Is Revolutionizing Medical Treatment

🤖 What Is AI in Healthcare? AI in healthcare refers to using machine learning, neural networks, and big data to improve medical care. It helps doctors diagnose faster, treat smarter, and monitor patients remotely. Applications include: Disease prediction Robot-assisted surgeries AI chatbots for symptom checking Automated image analysis (X-rays, MRIs, CT scans) 🧬 Faster and More Accurate…

[farmerstrend]

Why Most Kenyan Farmers Are Still Farming Blind: The Untold Problem of Soil Ignorance

Kenya’s agriculture is under pressure due to poor soil data and outdated fertiliser practices. Learn why digital soil testing and mapping could be the key to sustainable farming. There is a hidden crisis beneath our feet. Kenya’s agricultural potential is widely celebrated, yet beneath this promise lies a hidden crisis. Our soils are under pressure, and we don’t know them well enough to nurture…

[datastring]

Geospatial Solutions Market Set to Hit $2401.1 Billion by 2035

The global market for Geospatial Solutions is expected to experience significant growth, with industry revenue projected to rise from $488.0 billion in 2023 to $2401.1 billion by 2035. This reflects a compound annual growth rate (CAGR) of 14.2% from 2023 to 2035.

Detailed Analysis - https://datastringconsulting.com/industry-analysis/geospatial-solutions-market-research-report

Geospatial solutions are essential across a wide range of applications, including precision agriculture, urban planning, logistics and transportation, as well as defense and security. The market's growth is primarily driven by the increasing adoption of geospatial technologies in key sectors such as agriculture, urban development, and defense.

Competitive Landscape and Market Leadership

The Geospatial Solutions market is highly competitive, with several key players driving innovation and market penetration. Leading companies in the market include:

Esri

Hexagon Geospatial

Trimble

Topcon

HERE Technologies

Fugro

TomTom

Geo-Insights

Blue Marble Geographics

SuperMap

Mapbox

Cyient

These companies are at the forefront of advancing geospatial technologies, such as artificial intelligence (AI), machine learning, and real-time data analytics, which are helping to meet the growing demand for smarter and more efficient solutions across industries.

Key Growth Drivers and Market Opportunities

The growth of the Geospatial Solutions market is fueled by several factors:

Precision Agriculture: The growing need for efficient land use and sustainable farming practices is driving the demand for geospatial solutions in agriculture, enabling better crop management and resource allocation.

Urbanization and Smart City Initiatives: The increasing push for smart city development and urban planning requires geospatial technologies to manage infrastructure, transportation, and urban environments more efficiently.

Defense and Security: Geospatial solutions are playing a crucial role in defense and security applications, including surveillance, reconnaissance, and situational awareness.

Integration of AI and Machine Learning: The application of AI and machine learning in geospatial data analysis is enhancing the capabilities of these solutions, enabling real-time insights and decision-making.

Demand for Real-time Location Data: The growing reliance on real-time data in various sectors, including logistics, transportation, and emergency management, is driving the adoption of geospatial technologies.

Regional Dynamics and Supply Chain Evolution

North America and Asia-Pacific are the dominant regions in the Geospatial Solutions market. Both regions benefit from strong technological infrastructure, high levels of investment, and significant demand from key industries. However, emerging markets in India, Brazil, and South Africa are becoming increasingly important for market growth, driven by rapid urbanization, industrialization, and the adoption of new technologies.

Despite challenges such as high initial investments, data privacy concerns, and integration complexities, the geospatial solutions market’s supply chain—from data providers and software developers to system integrators and service providers—is expected to evolve to meet these challenges. Companies are also focusing on strategic advancements in developing regions to diversify revenue streams and expand their total addressable market (TAM).

About DataString Consulting

DataString Consulting is a leading provider of market research and business intelligence solutions, offering a comprehensive range of services for both B2C and B2B markets. With over 30 years of combined industry experience, DataString specializes in delivering actionable insights that support strategic decision-making.

The company’s expertise spans multiple industries, providing tailored research services in strategy consulting, opportunity assessment, competitive intelligence, and market forecasting. DataString Consulting helps businesses navigate complex markets and capitalize on emerging trends to achieve long-term success.

[goldsasa]

Deep dive.

I’ve been deeply immersed in research on water and data for weeks now. The more I read, the clearer it becomes: these two elements are more intertwined than we tend to think.

How do we treat something that flows? That connects? That stores memory?

Whether it’s molecules or megabytes — we might need to rethink the way we look at both.

More to come.

#Water #Data #PhilosophyOfTechnology #FutureThinking

[diagnozabam]

DeepSeek, Compromis de o Breșă Majoră de Securitate: Peste un Milion de Conversații Expuse Online

🚨 Un nou scandal de securitate zguduie lumea AI: DeepSeek, startup-ul chinez care a provocat neliniște pe burse la începutul săptămânii, a fost prins într-un incident grav de securitate. O bază de date neprotejată a fost descoperită expusă online, permițând accesul neautorizat la peste un milion de conversații private între utilizatori și chatbot-ul său, alături de informații tehnice…

[likitakans]

AI and Health: New Technologies Paving the Way for Better Treatment

Artificial intelligence (AI) is expanding rapidly in the health sector, and it is revolutionizing our medical system. With the help of AI, new technologies are being developed that are not only helpful in accurately diagnosing diseases but are also playing an important role in personalized treatment and management.

Quick and accurate diagnosis of diseases AI-based tools can now analyze medical imaging data such as X-rays, CT scans, and MRIs quickly and accurately. This helps doctors to quickly detect complex conditions such as cancer, heart diseases, and neurological problems.

Personalized medicine AI can help create personalized treatment plans for every individual by analyzing genomics and biometrics. This technology ensures that the patient gets the right medicine and the right dose at the right time.

Improved health management AI-based health apps and wearables such as smart watches are now helping people monitor their health condition. These devices regularly track health indicators such as heart rate, blood pressure and sleep quality.

Accelerating medical research The role of AI has become extremely important in the development of new drugs and vaccines. Using AI, scientists can analyze complex data sets and make new medical discoveries faster.

Accessible and affordable healthcare AI technology is helping in delivering affordable and effective healthcare, even in rural and remote areas. Telemedicine and virtual health assistants are bridging the gap between patients and doctors.

Conclusion Artificial intelligence is playing an important role in making healthcare more effective, accurate, and accessible. However, there are challenges such as data security and ethics in the use of AI technology which need to be dealt with. In the coming years, with more advanced and innovative uses of AI, the healthcare landscape may change completely.

[jcmarchi]

Eric Schmidt: AI misuse poses an ‘extreme risk’

New Post has been published on https://thedigitalinsider.com/eric-schmidt-ai-misuse-poses-an-extreme-risk/

Eric Schmidt: AI misuse poses an ‘extreme risk’

Eric Schmidt, former CEO of Google, has warned that AI misuse poses an “extreme risk” and could do catastrophic harm.

Speaking to BBC Radio 4’s Today programme, Schmidt cautioned that AI could be weaponised by extremists and “rogue states” such as North Korea, Iran, and Russia to “harm innocent people.”

Schmidt expressed concern that rapid AI advancements could be exploited to create weapons, including biological attacks. Highlighting the dangers, he said: “The real fears that I have are not the ones that most people talk about AI, I talk about extreme risk.”

Using a chilling analogy, Schmidt referenced the al-Qaeda leader responsible for the 9/11 attacks: “I’m always worried about the Osama bin Laden scenario, where you have some truly evil person who takes over some aspect of our modern life and uses it to harm innocent people.”

He emphasised the pace of AI development and its potential to be co-opted by nations or groups with malevolent intent.

“Think about North Korea, or Iran, or even Russia, who have some evil goal … they could misuse it and do real harm,” Schmidt warns.

Oversight without stifling innovation

Schmidt urged governments to closely monitor private tech companies pioneering AI research. While noting that tech leaders are generally aware of AI’s societal implications, they may make decisions based on different values from those of public officials.

“My experience with the tech leaders is that they do have an understanding of the impact they’re having, but they might make a different values judgement than the government would make.”

Schmidt also endorsed the export controls introduced under former US President Joe Biden last year to restrict the sale of advanced microchips. The measure is aimed at slowing the progress of geopolitical adversaries in AI research.  

Global divisions around preventing AI misuse

The tech veteran was in Paris when he made his remarks, attending the AI Action Summit, a two-day event that wrapped up on Tuesday.

The summit, attended by 57 countries, saw the announcement of an agreement on “inclusive” AI development. Signatories included major players like China, India, the EU, and the African Union.  

However, the UK and the US declined to sign the communique. The UK government said the agreement lacked “practical clarity” and failed to address critical “harder questions” surrounding national security. 

Schmidt cautioned against excessive regulation that might hinder progress in this transformative field. This was echoed by US Vice-President JD Vance who warned that heavy-handed regulation “would kill a transformative industry just as it’s taking off”.  

This reluctance to endorse sweeping international accords reflects diverging approaches to AI governance. The EU has championed a more restrictive framework for AI, prioritising consumer protections, while countries like the US and UK are opting for more agile and innovation-driven strategies. 

Schmidt pointed to the consequences of Europe’s tight regulatory stance, predicting that the region would miss out on pioneering roles in AI.

“The AI revolution, which is the most important revolution in my opinion since electricity, is not going to be invented in Europe,” he remarked.

Prioritising national and global safety

Schmidt’s comments come against a backdrop of increasing scrutiny over AI’s dual-use potential—its ability to be used for both beneficial and harmful purposes.

From deepfakes to autonomous weapons, AI poses a bevy of risks if left without measures to guard against misuse. Leaders and experts, including Schmidt, are advocating for a balanced approach that fosters innovation while addressing these dangers head-on.

While international cooperation remains a complex and contentious issue, the overarching consensus is clear: without safeguards, AI’s evolution could have unintended – and potentially catastrophic – consequences.

(Photo by Guillaume Paumier under CC BY 3.0 license. Cropped to landscape from original version.)

See also: NEPC: AI sprint risks environmental catastrophe

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

[insurance-brokers-india]

What are the next steps after obtaining an insurance broker license, and how can you generate potential leads using Mzapp CRM software?

Congratulations on securing your insurance broker license! The journey doesn’t end here; it’s just the beginning of building a successful insurance brokerage. Here’s how you can proceed and leverage Mzapp CRM software to find potential leads:

Steps After Getting Your Insurance Broker License

Understand Your Market: Research your target audience (individuals, businesses, or specific sectors).

Develop a Business Plan: Set goals for client acquisition, revenue, and operational processes.

Build a Network: Partner with insurance providers and attend industry events to establish your presence.

Create an Online Presence: Build a professional website and maintain active profiles on social platforms.

Offer Value-Added Services: Educate customers on policies, claims management, and risk assessments.

Using Mzapp CRM Software to Generate Leads

Lead Capture: Utilize Mzapp’s integrated forms and web tracking tools to capture inquiries from your website or social media.

Automated Follow-Ups: Set up personalized email and SMS follow-ups to nurture leads effectively.

Lead Scoring: Prioritize leads based on their interaction history, ensuring you focus on high-potential prospects.

Data-Driven Campaigns: Use analytics to identify what works and launch targeted campaigns.

Seamless Policy Management: Impress leads by showcasing how smoothly you manage policies and claims through Mzapp.

Why Choose Mzapp CRM?

Mzapp CRM simplifies lead management, streamlines operations, and provides insights into customer behavior, making it easier to convert prospects into loyal clients.

Learn more about how Mzapp can transform your insurance business here.

[mehmetyildizmelbourne-blog]

The Surprising Danger Lurking in Your Smart Glasses: A Wake-Up Call for Privacy

How Brilliant Innovations Can Be Misused and Abused, Causing Unnecessary Stress to the Public As a retired scientist and health advocate in many countries, I’ve had the privilege of witnessing incredible technological advances throughout my 53-year career in the healthcare industry. Privacy issues have always concerned me as they affect our mental health.  From early computing systems to the…

[trendtrackershq]

𝙄𝙣-𝘿𝙚𝙥𝙩𝙝 𝙎𝙩𝙪𝙙𝙮 𝙤𝙛 𝙩𝙝𝙚 𝙇𝙖𝙗𝙤𝙧𝙖𝙩𝙤𝙧𝙮 𝙄𝙣𝙛𝙤𝙧𝙢𝙖𝙩𝙞𝙤𝙣 𝙈𝙖𝙣𝙖𝙜𝙚𝙢𝙚𝙣𝙩 𝙎𝙮𝙨𝙩𝙚𝙢 (𝙇𝙄𝙈𝙎) 𝙈𝙖𝙧𝙠𝙚𝙩

𝙂𝙚𝙩 𝙖 𝙁𝙍𝙀𝙀 𝙎𝙖𝙢𝙥𝙡𝙚: https://www.nextmsc.com/laboratory-information-management-system-market/request-sample

As the world of laboratory management continues to evolve, the 𝙇𝙖𝙗𝙤𝙧𝙖𝙩𝙤𝙧𝙮 𝙄𝙣𝙛𝙤𝙧𝙢𝙖𝙩𝙞𝙤𝙣 𝙈𝙖𝙣𝙖𝙜𝙚𝙢𝙚𝙣𝙩 𝙎𝙮𝙨𝙩𝙚𝙢 (𝙇𝙄𝙈𝙎) 𝙈𝙖𝙧𝙠𝙚𝙩 is experiencing transformative growth. With advancements in technology and an increased focus on efficiency and data integrity, LIMS solutions are becoming indispensable across various industries.

𝙆𝙚𝙮 𝙄𝙣𝙨𝙞𝙜𝙝𝙩𝙨:

𝙈𝙖𝙧𝙠𝙚𝙩 𝙀𝙭𝙥𝙖𝙣𝙨𝙞𝙤𝙣: The LIMS market is on a rapid ascent, driven by the need for streamlined operations and enhanced data management.

𝙏𝙚𝙘𝙝𝙣𝙤𝙡𝙤𝙜𝙞𝙘𝙖𝙡 𝙄𝙣𝙣𝙤𝙫𝙖𝙩𝙞𝙤𝙣𝙨: Integration with cloud computing, AI, and IoT is revolutionizing how laboratories manage and analyze data.

𝙍𝙚𝙜𝙪𝙡𝙖𝙩𝙤𝙧𝙮 𝘾𝙤𝙢𝙥𝙡𝙞𝙖𝙣𝙘𝙚: Enhanced capabilities to meet stringent regulatory requirements are propelling the adoption of LIMS.

𝙒𝙝𝙮 𝙄𝙩 𝙈𝙖𝙩𝙩𝙚𝙧𝙨: Efficiency & Accuracy: LIMS solutions optimize workflow, reduce errors, and ensure precise data tracking.

𝘿𝙖𝙩𝙖 𝙎𝙚𝙘𝙪𝙧𝙞𝙩𝙮: Advanced systems offer robust security features to protect sensitive information.

𝙎𝙘𝙖𝙡𝙖𝙗𝙞𝙡𝙞𝙩𝙮: LIMS can be tailored to meet the needs of small labs and large research facilities alike.

𝙆𝙚𝙮 𝙋𝙡𝙖𝙮𝙚𝙧𝙨:

Thermo Fisher Scientific

LabWare

The Chatterjee Group

McKesson Corporation

LabLynx

Computing Solutions

Labworks LLC

Illumina

Novatek International

Agilent Technologies, Inc.

𝘼𝙘𝙘𝙚𝙨𝙨 𝙁𝙪𝙡𝙡 𝙍𝙚𝙥𝙤𝙧𝙩: https://www.nextmsc.com/report/laboratory-information-management-system-market

As we look towards the future, the LIMS market is poised for continued innovation and growth, paving the way for more efficient and effective laboratory management.

Let’s stay ahead of the curve and explore the exciting opportunities within the LIMS landscape!

[louistonehill]

A new tool lets artists add invisible changes to the pixels in their art before they upload it online so that if it’s scraped into an AI training set, it can cause the resulting model to break in chaotic and unpredictable ways. 

The tool, called Nightshade, is intended as a way to fight back against AI companies that use artists’ work to train their models without the creator’s permission. Using it to “poison” this training data could damage future iterations of image-generating AI models, such as DALL-E, Midjourney, and Stable Diffusion, by rendering some of their outputs useless—dogs become cats, cars become cows, and so forth. MIT Technology Review got an exclusive preview of the research, which has been submitted for peer review at computer security conference Usenix.   

AI companies such as OpenAI, Meta, Google, and Stability AI are facing a slew of lawsuits from artists who claim that their copyrighted material and personal information was scraped without consent or compensation. Ben Zhao, a professor at the University of Chicago, who led the team that created Nightshade, says the hope is that it will help tip the power balance back from AI companies towards artists, by creating a powerful deterrent against disrespecting artists’ copyright and intellectual property. Meta, Google, Stability AI, and OpenAI did not respond to MIT Technology Review’s request for comment on how they might respond. 

Zhao’s team also developed Glaze, a tool that allows artists to “mask” their own personal style to prevent it from being scraped by AI companies. It works in a similar way to Nightshade: by changing the pixels of images in subtle ways that are invisible to the human eye but manipulate machine-learning models to interpret the image as something different from what it actually shows. 

Continue reading article here

[yeoldenews]

A Guide to Historically Accurate Regency-Era Names

I recently received a message from a historical romance writer asking if I knew any good resources for finding historically accurate Regency-era names for their characters.

Not knowing any off the top of my head, I dug around online a bit and found there really isn’t much out there. The vast majority of search results were Buzzfeed-style listicles which range from accurate-adjacent to really, really, really bad.

I did find a few blog posts with fairly decent name lists, but noticed that even these have very little indication as to each name’s relative popularity as those statistical breakdowns really don't exist.

I began writing up a response with this information, but then I (being a research addict who was currently snowed in after a blizzard) thought hey - if there aren’t any good resources out there why not make one myself?

As I lacked any compiled data to work from, I had to do my own data wrangling on this project. Due to this fact, I limited the scope to what I thought would be the most useful for writers who focus on this era, namely - people of a marriageable age living in the wealthiest areas of London.

So with this in mind - I went through period records and compiled the names of 25,000 couples who were married in the City of Westminster (which includes Mayfair, St. James and Hyde Park) between 1804 to 1821.

So let’s see what all that data tells us…

To begin - I think it’s hard for us in the modern world with our wide and varied abundance of first names to conceive of just how POPULAR popular names of the past were.

If you were to take a modern sample of 25-year-old (born in 1998) American women, the most common name would be Emily with 1.35% of the total population. If you were to add the next four most popular names (Hannah, Samantha, Sarah and Ashley) these top five names would bring you to 5.5% of the total population. (source: Social Security Administration)

If you were to do the same survey in Regency London - the most common name would be Mary with 19.2% of the population. Add the next four most popular names (Elizabeth, Ann, Sarah and Jane) and with just 5 names you would have covered 62% of all women.

To hit 62% of the population in the modern survey it would take the top 400 names.

The top five Regency men’s names (John, William, Thomas, James and George) have nearly identical statistics as the women’s names.

I struggled for the better part of a week with how to present my findings, as a big list in alphabetical order really fails to get across the popularity factor and also isn’t the most tumblr-compatible format. And then my YouTube homepage recommended a random video of someone ranking all the books they’d read last year - and so I present…

The Regency Name Popularity Tier List

The Tiers

S+ - 10% of the population or greater. There is no modern equivalent to this level of popularity. 52% of the population had one of these 7 names.

S - 2-10%. There is still no modern equivalent to this level of popularity. Names in this percentage range in the past have included Mary and William in the 1880s and Jennifer in the late 1970s (topped out at 4%).

A - 1-2%. The top five modern names usually fall in this range. Kids with these names would probably include their last initial in class to avoid confusion. (1998 examples: Emily, Sarah, Ashley, Michael, Christopher, Brandon.)

B - .3-1%. Very common names. Would fall in the top 50 modern names. You would most likely know at least 1 person with these names. (1998 examples: Jessica, Megan, Allison, Justin, Ryan, Eric)

C - .17-.3%. Common names. Would fall in the modern top 100. You would probably know someone with these names, or at least know of them. (1998 examples: Chloe, Grace, Vanessa, Sean, Spencer, Seth)

D - .06-.17%. Less common names. In the modern top 250. You may not personally know someone with these names, but you’re aware of them. (1998 examples: Faith, Cassidy, Summer, Griffin, Dustin, Colby)

E - .02-.06%. Uncommon names. You’re aware these are names, but they are not common. Unusual enough they may be remarked upon. (1998 examples: Calista, Skye, Precious, Fabian, Justice, Lorenzo)

F - .01-.02%. Rare names. You may have heard of these names, but you probably don’t know anyone with one. Extremely unusual, and would likely be remarked upon. (1998 examples: Emerald, Lourdes, Serenity, Dario, Tavian, Adonis)

G - Very rare names. There are only a handful of people with these names in the entire country. You’ve never met anyone with this name.

H - Virtually non-existent. Names that theoretically could have existed in the Regency period (their original source pre-dates the early 19th century) but I found fewer than five (and often no) period examples of them being used in Regency England. (Example names taken from romance novels and online Regency name lists.)

Just to once again reinforce how POPULAR popular names were before we get to the tier lists - statistically, in a ballroom of 100 people in Regency London: 80 would have names from tiers S+/S. An additional 15 people would have names from tiers A/B and C. 4 of the remaining 5 would have names from D/E. Only one would have a name from below tier E.

Women's Names

S+ Mary, Elizabeth, Ann, Sarah      

S - Jane, Mary Ann+, Hannah, Susannah, Margaret, Catherine, Martha, Charlotte, Maria

A - Frances, Harriet, Sophia, Eleanor, Rebecca

B - Alice, Amelia, Bridget~, Caroline, Eliza, Esther, Isabella, Louisa, Lucy, Lydia, Phoebe, Rachel, Susan

C - Ellen, Fanny*, Grace, Henrietta, Hester, Jemima, Matilda, Priscilla

D - Abigail, Agnes, Amy, Augusta, Barbara, Betsy*, Betty*, Cecilia, Christiana, Clarissa, Deborah, Diana, Dinah, Dorothy, Emily, Emma, Georgiana, Helen, Janet^, Joanna, Johanna, Judith, Julia, Kezia, Kitty*, Letitia, Nancy*, Ruth, Winifred>

E - Arabella, Celia, Charity, Clara, Cordelia, Dorcas, Eve, Georgina, Honor, Honora, Jennet^, Jessie*^, Joan, Joyce, Juliana, Juliet, Lavinia, Leah, Margery, Marian, Marianne, Marie, Mercy, Miriam, Naomi, Patience, Penelope, Philadelphia, Phillis, Prudence, Rhoda, Rosanna, Rose, Rosetta, Rosina, Sabina, Selina, Sylvia, Theodosia, Theresa

F - (selected) Alicia, Bethia, Euphemia, Frederica, Helena, Leonora, Mariana, Millicent, Mirah, Olivia, Philippa, Rosamund, Sybella, Tabitha, Temperance, Theophila, Thomasin, Tryphena, Ursula, Virtue, Wilhelmina

G - (selected) Adelaide, Alethia, Angelina, Cassandra, Cherry, Constance, Delilah, Dorinda, Drusilla, Eva, Happy, Jessica, Josephine, Laura, Minerva, Octavia, Parthenia, Theodora, Violet, Zipporah

H - Alberta, Alexandra, Amber, Ashley, Calliope, Calpurnia, Chloe, Cressida, Cynthia, Daisy, Daphne, Elaine, Eloise, Estella, Lilian, Lilias, Francesca, Gabriella, Genevieve, Gwendoline, Hermione, Hyacinth, Inez, Iris, Kathleen, Madeline, Maude, Melody, Portia, Seabright, Seraphina, Sienna, Verity

Men's Names

S+ John, William, Thomas

S - James, George, Joseph, Richard, Robert, Charles, Henry, Edward, Samuel

A - Benjamin, (Mother’s/Grandmother’s maiden name used as first name)#

B - Alexander^, Andrew, Daniel, David>, Edmund, Francis, Frederick, Isaac, Matthew, Michael, Patrick~, Peter, Philip, Stephen, Timothy

C - Abraham, Anthony, Christopher, Hugh>, Jeremiah, Jonathan, Nathaniel, Walter

D - Adam, Arthur, Bartholomew, Cornelius, Dennis, Evan>, Jacob, Job, Josiah, Joshua, Lawrence, Lewis, Luke, Mark, Martin, Moses, Nicholas, Owen>, Paul, Ralph, Simon

E - Aaron, Alfred, Allen, Ambrose, Amos, Archibald, Augustin, Augustus, Barnard, Barney, Bernard, Bryan, Caleb, Christian, Clement, Colin, Duncan^, Ebenezer, Edwin, Emanuel, Felix, Gabriel, Gerard, Gilbert, Giles, Griffith, Harry*, Herbert, Humphrey, Israel, Jabez, Jesse, Joel, Jonas, Lancelot, Matthias, Maurice, Miles, Oliver, Rees, Reuben, Roger, Rowland, Solomon, Theophilus, Valentine, Zachariah

F - (selected) Abel, Barnabus, Benedict, Connor, Elijah, Ernest, Gideon, Godfrey, Gregory, Hector, Horace, Horatio, Isaiah, Jasper, Levi, Marmaduke, Noah, Percival, Shadrach, Vincent

G - (selected) Albion, Darius, Christmas, Cleophas, Enoch, Ethelbert, Gavin, Griffin, Hercules, Hugo, Innocent, Justin, Maximilian, Methuselah, Peregrine, Phineas, Roland, Sebastian, Sylvester, Theodore, Titus, Zephaniah

H - Albinus, Americus, Cassian, Dominic, Eric, Milo, Rollo, Trevor, Tristan, Waldo, Xavier

# Men were sometimes given a family surname (most often their mother's or grandmother's maiden name) as their first name - the most famous example of this being Fitzwilliam Darcy. If you were to combine all surname-based first names as a single 'name' this is where the practice would rank.

*Rank as a given name, not a nickname

+If you count Mary Ann as a separate name from Mary - Mary would remain in S+ even without the Mary Anns included

~Primarily used by people of Irish descent

^Primarily used by people of Scottish descent

>Primarily used by people of Welsh descent

I was going to continue on and write about why Regency-era first names were so uniform, discuss historically accurate surnames, nicknames, and include a little guide to finding 'unique' names that are still historically accurate - but this post is already very, very long, so that will have to wait for a later date.

If anyone has any questions/comments/clarifications in the meantime feel free to message me.

Methodology notes: All data is from marriage records covering six parishes in the City of Westminster between 1804 and 1821. The total sample size was 50,950 individuals.

I chose marriage records rather than births/baptisms as I wanted to focus on individuals who were adults during the Regency era rather than newborns. I think many people make the mistake when researching historical names by using baby name data for the year their story takes place rather than 20 to 30 years prior, and I wanted to avoid that. If you are writing a story that takes place in 1930 you don’t want to research the top names for 1930, you need to be looking at 1910 or earlier if you are naming adult characters.

I combined (for my own sanity) names that are pronounced identically but have minor spelling differences: i.e. the data for Catherine also includes Catharines and Katherines, Susannah includes Susannas, Phoebe includes Phebes, etc.

The compound 'Mother's/Grandmother's maiden name used as first name' designation is an educated guesstimate based on what I recognized as known surnames, as I do not hate myself enough to go through 25,000+ individuals and confirm their mother's maiden names. So if the tally includes any individuals who just happened to be named Fitzroy/Hastings/Townsend/etc. because their parents liked the sound of it and not due to any familial relations - my bad.

I did a small comparative survey of 5,000 individuals in several rural communities in Rutland and Staffordshire (chosen because they had the cleanest data I could find and I was lazy) to see if there were any significant differences between urban and rural naming practices and found the results to be very similar. The most noticeable difference I observed was that the S+ tier names were even MORE popular in rural areas than in London. In Rutland between 1810 and 1820 Elizabeths comprised 21.4% of all brides vs. 15.3% in the London survey. All other S+ names also saw increases of between 1% and 6%. I also observed that the rural communities I surveyed saw a small, but noticeable and fairly consistent, increase in the use of names with Biblical origins.

Sources of the records I used for my survey: 

Ancestry.com. England & Wales Marriages, 1538-1988 [database on-line].

Ancestry.com. Westminster, London, England, Church of England Marriages and Banns, 1754-1935 [database on-line].

[neosciencehub]

Neuralink's Human Trials: Regulatory Hurdles of Neurotechnology

Neuralink's Human Trials: Regulatory Hurdles of Neurotechnology @neosciencehub #neosciencehub #science #neuralink #humantrails #neurotechnology #elonmusk #FDA #healthcare #medicalscience #ClinicalResearch #health #AITech #BrainComputer #DataPrivacy #NSH

The journey of Neuralink, Elon Musk’s ambitious neurotechnology venture, to its first human trials represents a significant achievement in the field of biomedical innovation. However, this path was not without its challenges. Neo Science Hub’s Scientific Advisory Team examines the intricate regulatory landscape that companies like Neuralink must navigate, highlighting the complex interplay of…

[jcmarchi]

Sam Altman, OpenAI: The superintelligence era has begun

New Post has been published on https://thedigitalinsider.com/sam-altman-openai-the-superintelligence-era-has-begun/

Sam Altman, OpenAI: The superintelligence era has begun

OpenAI chief Sam Altman has declared that humanity has crossed into the era of artificial superintelligence—and there’s no turning back.

“We are past the event horizon; the takeoff has started,” Altman states. “Humanity is close to building digital superintelligence, and at least so far it’s much less weird than it seems like it should be.”

The lack of visible signs – robots aren’t yet wandering our high streets, disease remains unconquered – masks what Altman characterises as a profound transformation already underway. Behind closed doors at tech firms like his own, systems are emerging that can outmatch general human intellect.

“In some big sense, ChatGPT is already more powerful than any human who has ever lived,” Altman claims, noting that “hundreds of millions of people rely on it every day and for increasingly important tasks.”

This casual observation hints at a troubling reality: such systems already wield enormous influence, with even minor flaws potentially causing widespread harm when multiplied across their vast user base.

The road to superintelligence

Altman outlines a timeline towards superintelligence that might leave many readers checking their calendars.

By next year, he expects “the arrival of agents that can do real cognitive work,” fundamentally transforming software development. The following year could bring “systems that can figure out novel insights”—meaning AI that generates original discoveries rather than merely processing existing knowledge. By 2027, we might see “robots that can do tasks in the real world.”

Each prediction seems to leap beyond the previous one in capability, drawing a line that points unmistakably toward superintelligence—systems whose intellectual capacity vastly outstrips human potential across most domains.

“We do not know how far beyond human-level intelligence we can go, but we are about to find out,” Altman states.

This progression has sparked fierce debate among experts, with some arguing these capabilities remain decades away. Yet Altman’s timeline suggests OpenAI has internal evidence for this accelerated path that isn’t yet public knowledge.

A feedback loop that changes everything

What makes current AI development uniquely concerning is what Altman calls a “larval version of recursive self-improvement”—the ability of today’s AI to help researchers build tomorrow’s more capable systems.

“Advanced AI is interesting for many reasons, but perhaps nothing is quite as significant as the fact that we can use it to do faster AI research,” he explains. “If we can do a decade’s worth of research in a year, or a month, then the rate of progress will obviously be quite different.”

This acceleration compounds as multiple feedback loops intersect. Economic value drives infrastructure development, which enables more powerful systems, which generate more economic value. Meanwhile, the creation of physical robots capable of manufacturing more robots could create another explosive cycle of growth.

“The rate of new wonders being achieved will be immense,” Altman predicts. “It’s hard to even imagine today what we will have discovered by 2035; maybe we will go from solving high-energy physics one year to beginning space colonisation the next year.”

Such statements would sound like hyperbole from almost anyone else. Coming from the man overseeing some of the most advanced AI systems on the planet, they demand at least some consideration.

Living alongside superintelligence

Despite the potential impact, Altman believes many aspects of human life will retain their familiar contours. People will still form meaningful relationships, create art, and enjoy simple pleasures.

But beneath these constants, society faces profound disruption. “Whole classes of jobs” will disappear—potentially at a pace that outstrips our ability to create new roles or retrain workers. The silver lining, according to Altman, is that “the world will be getting so much richer so quickly that we’ll be able to seriously entertain new policy ideas we never could before.”

For those struggling to imagine this future, Altman offers a thought experiment: “A subsistence farmer from a thousand years ago would look at what many of us do and say we have fake jobs, and think that we are just playing games to entertain ourselves since we have plenty of food and unimaginable luxuries.”

Our descendants may view our most prestigious professions with similar bemusement.

The alignment problem

Amid these predictions, Altman identifies a challenge that keeps AI safety researchers awake at night: ensuring superintelligent systems remain aligned with human values and intentions.

Altman states the need to solve “the alignment problem, meaning that we can robustly guarantee that we get AI systems to learn and act towards what we collectively really want over the long-term”. He contrasts this with social media algorithms that maximise engagement by exploiting psychological vulnerabilities.

This isn’t merely a technical issue but an existential one. If superintelligence emerges without robust alignment, the consequences could be devastating. Yet defining “what we collectively really want” will be almost impossible in a diverse global society with competing values and interests.

“The sooner the world can start a conversation about what these broad bounds are and how we define collective alignment, the better,” Altman urges.

OpenAI is building a global brain

Altman has repeatedly characterised what OpenAI is building as “a brain for the world.”

This isn’t meant metaphorically. OpenAI and its competitors are creating cognitive systems intended to integrate into every aspect of human civilisation—systems that, by Altman’s own admission, will exceed human capabilities across domains.

“Intelligence too cheap to meter is well within grasp,” Altman states, suggesting that superintelligent capabilities will eventually become as ubiquitous and affordable as electricity.

For those dismissing such claims as science fiction, Altman offers a reminder that merely a few years ago, today’s AI capabilities seemed equally implausible: “If we told you back in 2020 we were going to be where we are today, it probably sounded more crazy than our current predictions about 2030.”

As the AI industry continues its march toward superintelligence, Altman’s closing wish – “May we scale smoothly, exponentially, and uneventfully through superintelligence” – sounds less like a prediction and more like a prayer.

While timelines may (and will) be disputed, the OpenAI chief makes clear the race toward superintelligence isn’t coming—it’s already here. Humanity must grapple with what that means.

See also: Magistral: Mistral AI challenges big tech with reasoning model

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.