#Data Science and AI Platforms

[chandantripathi889]

Top Data Science and AI Platforms in 2024: Revolutionizing Innovation and Decision-Making

Introduction: The Role of Data and AI in 2024

In 2024, data drives decisions while artificial intelligence (AI) drives innovation. Choosing the right platform to harness the power of data and AI is critical for staying competitive. Both companies and professionals are seeking platforms that support seamless data science projects and advanced AI model development.

This article explores the top data science and AI platforms of 2024, with a special focus on Manipal AI Platforms, a rising star in the tech world.

Why Choose Data Science and AI Platforms?

Before delving into specific platforms, it’s important to understand why these tools have become essential in today's business landscape:

Accelerate Decision-Making: Data science platforms offer actionable insights, enabling faster and more informed decisions.

Automation and Efficiency: AI platforms automate routine tasks, freeing businesses to focus on more strategic issues.

Innovation Hub: Many platforms allow users to experiment with cutting-edge AI models, fostering continuous innovation.

Image alt tag - AI platforms

Reference - https://www.fotor.com/blog/ai-platform/ 

Top Data Science and AI Platforms in 2024

1. Manipal AI Platforms

Manipal AI Platforms bridge the gap between education and industry needs, offering tools for both novices and experienced data scientists.

Key Features:

Ease of Use: User-friendly interfaces make the platform accessible to users of all experience levels.

Scalability: Whether you're a startup or a large enterprise, the platform offers solutions that grow with your business.

Industry Integration: The platform seamlessly integrates with industry-specific tools, making it ideal for projects in healthcare, finance, and more.

Ease of Use - User-friendly dashboards for all experience levels.

Scalability - Tailored solutions for businesses of any size.

Industry-Specific Tools - Supports real-world business challenges in industries like healthcare and finance.

2. IBM Watson Studio

IBM Watson Studio is a powerful platform for operationalizing AI at scale.

Key Features:

Customizable AI Models: Users can build their own AI models or utilize pre-built ones for quick deployment.

Data Governance: Strong focus on data privacy and security, making it ideal for industries handling sensitive data like finance and healthcare.

3. Google Cloud AI Platform

Google Cloud AI Platform offers a comprehensive suite of AI and machine learning services.

Key Features:

Collaboration and Flexibility: Seamless collaboration with shared datasets and models.

Powerful APIs: Enables developers to easily integrate advanced AI capabilities into applications.

4. Microsoft Azure AI

Microsoft Azure AI is well-known for its extensive range of AI tools.

Key Features:

AI for Every Developer: Tools for developers at all levels to create, train, and deploy AI models.

Seamless Integration: Part of the Azure ecosystem, integrating effortlessly with Microsoft services like Azure DevOps and Teams.

5. Amazon SageMaker

Amazon SageMaker is a fully managed platform that allows developers and data scientists to quickly build, train, and deploy machine learning models.

Key Features:

Comprehensive Machine Learning: Offers everything from data labeling to model monitoring.

Cost-Efficiency: Robust infrastructure that allows businesses to scale AI operations while maintaining cost-efficiency.

Future Trends in Data Science and AI

As we move further into 2024, several trends are shaping the future of data science and AI:

Explainable AI (XAI): Increasing demand for transparency and explainability in AI systems.

AI for Sustainability: AI will play a major role in solving environmental challenges, focusing on energy efficiency, waste reduction, and carbon footprint management.

AI and Data Ethics: The importance of ethical AI usage, particularly regarding data privacy, will remain a key discussion point.

Conclusion: Which Platform Should You Choose?

Selecting the right platform depends on your unique requirements:

Manipal AI Platforms: Ideal for scaling and industry-specific tools.

IBM Watson Studio: Known for strong security and data governance.

Google Cloud AI: Best for collaboration and flexibility.

Microsoft Azure AI: Great for seamless integration with Microsoft tools.

Amazon SageMaker: Perfect for businesses looking for comprehensive, scalable AI solutions.

As AI and data science continue to revolutionize industries, platforms like Manipal AI Platforms are setting new benchmarks. Their industry-specific tools and accessibility are helping professionals succeed in this fast-evolving space.

For more information on these cutting-edge platforms, visit IIT Roorkee.

[bigleapblog]

Your Guide to B.Tech in Computer Science & Engineering Colleges

In today's technology-driven world, pursuing a B.Tech in Computer Science and Engineering (CSE) has become a popular choice among students aspiring for a bright future. The demand for skilled professionals in areas like Artificial Intelligence, Machine Learning, Data Science, and Cloud Computing has made computer science engineering colleges crucial in shaping tomorrow's innovators. Saraswati College of Engineering (SCOE), a leader in engineering education, provides students with a perfect platform to build a successful career in this evolving field.

Whether you're passionate about coding, software development, or the latest advancements in AI, pursuing a B.Tech in Computer Science and Engineering at SCOE can open doors to endless opportunities.

Why Choose B.Tech in Computer Science and Engineering?

Choosing a B.Tech in Computer Science and Engineering isn't just about learning to code; it's about mastering problem-solving, logical thinking, and the ability to work with cutting-edge technologies. The course offers a robust foundation that combines theoretical knowledge with practical skills, enabling students to excel in the tech industry.

At SCOE, the computer science engineering courses are designed to meet industry standards and keep up with the rapidly evolving tech landscape. With its AICTE Approved, NAAC Accredited With Grade-"A+" credentials, the college provides quality education in a nurturing environment. SCOE's curriculum goes beyond textbooks, focusing on hands-on learning through projects, labs, workshops, and internships. This approach ensures that students graduate not only with a degree but with the skills needed to thrive in their careers.

The Role of Computer Science Engineering Colleges in Career Development

The role of computer science engineering colleges like SCOE is not limited to classroom teaching. These institutions play a crucial role in shaping students' futures by providing the necessary infrastructure, faculty expertise, and placement opportunities. SCOE, established in 2004, is recognized as one of the top engineering colleges in Navi Mumbai. It boasts a strong placement record, with companies like Goldman Sachs, Cisco, and Microsoft offering lucrative job opportunities to its graduates.

The computer science engineering courses at SCOE are structured to provide a blend of technical and soft skills. From the basics of computer programming to advanced topics like Artificial Intelligence and Data Science, students at SCOE are trained to be industry-ready. The faculty at SCOE comprises experienced professionals who not only impart theoretical knowledge but also mentor students for real-world challenges.

Highlights of the B.Tech in Computer Science and Engineering Program at SCOE

Comprehensive Curriculum: The B.Tech in Computer Science and Engineering program at SCOE covers all major areas, including programming languages, algorithms, data structures, computer networks, operating systems, AI, and Machine Learning. This ensures that students receive a well-rounded education, preparing them for various roles in the tech industry.

Industry-Relevant Learning: SCOE’s focus is on creating professionals who can immediately contribute to the tech industry. The college regularly collaborates with industry leaders to update its curriculum, ensuring students learn the latest technologies and trends in computer science engineering.

State-of-the-Art Infrastructure: SCOE is equipped with modern laboratories, computer centers, and research facilities, providing students with the tools they need to gain practical experience. The institution’s infrastructure fosters innovation, helping students work on cutting-edge projects and ideas during their B.Tech in Computer Science and Engineering.

Practical Exposure: One of the key benefits of studying at SCOE is the emphasis on practical learning. Students participate in hands-on projects, internships, and industry visits, giving them real-world exposure to how technology is applied in various sectors.

Placement Support: SCOE has a dedicated placement cell that works tirelessly to ensure students secure internships and job offers from top companies. The B.Tech in Computer Science and Engineering program boasts a strong placement record, with top tech companies visiting the campus every year. The highest on-campus placement offer for the academic year 2022-23 was an impressive 22 LPA from Goldman Sachs, reflecting the college’s commitment to student success.

Personal Growth: Beyond academics, SCOE encourages students to participate in extracurricular activities, coding competitions, and tech fests. These activities enhance their learning experience, promote teamwork, and help students build a well-rounded personality that is essential in today’s competitive job market.

What Makes SCOE Stand Out?

With so many computer science engineering colleges to choose from, why should you consider SCOE for your B.Tech in Computer Science and Engineering? Here are a few factors that make SCOE a top choice for students:

Experienced Faculty: SCOE prides itself on having a team of highly qualified and experienced faculty members. The faculty’s approach to teaching is both theoretical and practical, ensuring students are equipped to tackle real-world challenges.

Strong Industry Connections: The college maintains strong relationships with leading tech companies, ensuring that students have access to internship opportunities and campus recruitment drives. This gives SCOE graduates a competitive edge in the job market.

Holistic Development: SCOE believes in the holistic development of students. In addition to academic learning, the college offers opportunities for personal growth through various student clubs, sports activities, and cultural events.

Supportive Learning Environment: SCOE provides a nurturing environment where students can focus on their academic and personal growth. The campus is equipped with modern facilities, including spacious classrooms, labs, a library, and a recreation center.

Career Opportunities After B.Tech in Computer Science and Engineering from SCOE

Graduates with a B.Tech in Computer Science and Engineering from SCOE are well-prepared to take on various roles in the tech industry. Some of the most common career paths for CSE graduates include:

Software Engineer: Developing software applications, web development, and mobile app development are some of the key responsibilities of software engineers. This role requires strong programming skills and a deep understanding of software design.

Data Scientist: With the rise of big data, data scientists are in high demand. CSE graduates with knowledge of data science can work on data analysis, machine learning models, and predictive analytics.

AI Engineer: Artificial Intelligence is revolutionizing various industries, and AI engineers are at the forefront of this change. SCOE’s curriculum includes AI and Machine Learning, preparing students for roles in this cutting-edge field.

System Administrator: Maintaining and managing computer systems and networks is a crucial role in any organization. CSE graduates can work as system administrators, ensuring the smooth functioning of IT infrastructure.

Cybersecurity Specialist: With the growing threat of cyberattacks, cybersecurity specialists are essential in protecting an organization’s digital assets. CSE graduates can pursue careers in cybersecurity, safeguarding sensitive information from hackers.

Conclusion: Why B.Tech in Computer Science and Engineering at SCOE is the Right Choice

Choosing the right college is crucial for a successful career in B.Tech in Computer Science and Engineering. Saraswati College of Engineering (SCOE) stands out as one of the best computer science engineering colleges in Navi Mumbai. With its industry-aligned curriculum, state-of-the-art infrastructure, and excellent placement record, SCOE offers students the perfect environment to build a successful career in computer science.

Whether you're interested in AI, data science, software development, or any other field in computer science, SCOE provides the knowledge, skills, and opportunities you need to succeed. With a strong focus on hands-on learning and personal growth, SCOE ensures that students graduate not only as engineers but as professionals ready to take on the challenges of the tech world.

If you're ready to embark on an exciting journey in the world of technology, consider pursuing your B.Tech in Computer Science and Engineering at SCOE—a college where your future takes shape.

[codecrafted]

10 Biggest Data Science Trends to Watch in 2025 Data science is evolving faster than ever! From generative AI and real-time analytics to edge computing and ethical AI, 2025 is set to bring groundbreaking changes. 🌐💡

Whether you're a data enthusiast, professional, or just curious, this list breaks down the biggest trends reshaping how businesses and tech teams work with data. Learn about synthetic data, low-code tools, quantum computing’s potential, and more.

[jcmarchi]

AI enables shift from enablement to strategic leadership

New Post has been published on https://thedigitalinsider.com/ai-enables-shift-from-enablement-to-strategic-leadership/

AI enables shift from enablement to strategic leadership

CIOs and business leaders know they’re sitting on a goldmine of business data. And while traditional tools such as business intelligence platforms and statistical analysis software can effectively surface insights from the collated data resources, doing so quickly, in real-time and at scale remains an unsolved challenge.

Enterprise AI, when deployed responsibly and at scale, can turn these bottlenecks into opportunities. Acting quickly on data, even ‘live’ (during a customer interaction, for example), is one of the technology’s abilities, as is scalability: AI can process large amounts of information from disparate sources almost as easily as it can summarize a one-page spreadsheet.

But deploying an AI solution in the modern enterprise isn’t simple. It takes structure, trust and the right talent. Along with the practical implementation challenges, using AI brings its own challenges, such as data governance, the need to impose guardrails on AI responses and training data, and persistent staffing issues.

We met with Rani Radhakrishnan, PwC Principal, Technology Managed Services – AI, Data Analytics and Insights, to talk candidly about what’s working — and what’s holding back CIOs in their AI journey. We spoke ahead of her speaking engagement at TechEx AI & Big Data Expo North America, June 4 and 5, at the Santa Clara Convention Center.

Rani is especially attuned to some of the governance, data privacy and sovereignty issues that face enterprises, having spent many years in her career working with numerous clients in the health sector — an area where issues like privacy, data oversight and above all data accuracy are make-or-break aspects of technology deployments.

“It’s not enough to just have a prompt engineer or a Python developer. … You still need the human in the loop to curate the right training data sets, review and address any bias in the outputs.” —Rani Radhakrishnan, PwC

From support to strategy: shifting expectations for AI

Rani said that there’s a growing enthusiasm from PwC’s clients for AI-powered managed services that can provide both business insights in every sector, and for the technology to be used more proactively, in so-called agentic roles where agents can independently act on data and user input; where autonomous AI agents can take action based on interactions with humans, access to data resources and automation.

For example, PwC’s agent OS is a modular AI platform that connects systems and scales intelligent agents into workflows, many times faster than traditional computing methods. It’s an example of how PwC responds to the demand for AI from its clients, many of whom see the potential of this new technology, but lack the in-house expertise and staff to act on their needs.

Depending on the sector of the organization, the interest in AI can come from many different places in the business. Proactive monitoring of physical or digital systems; predictive maintenance in manufacturing or engineering; or cost efficiencies won by automation in complex, customer-facing environments, are just a few examples.

But regardless of where AI can bring value, most companies don’t yet have in-house the range of skills and people necessary for effective AI deployment — or at least, deployments that achieve ROI and don’t come with significant risk.

“It’s not enough to just have a prompt engineer or a Python developer,” Rani said. “You’ve got to put all of these together in a very structured manner, and you still need the human in the loop to curate the right training data sets, review and address any bias in the outputs.”

Cleaning house: the data challenge behind AI

Rani says that effective AI implementations need a mix of technical skills — data engineering, data science, prompt engineering — in combination with an organization’s domain expertise. Internal domain expertise can define the right outcomes, and technical staff can cover the responsible AI practices, like data collation and governance, and confirm that AI systems work responsibly and within company guidelines.

“In order to get the most value out of AI, an organization has to get the underlying data right,” she said. “I don’t know of a single company that says its data is in great shape … you’ve got to get it into the right structure and normalize it properly so you can query, analyze, and annotate it and identify emerging trends.”

Part of the work enterprises have to put in for effective AI use is the observation for and correction of bias — in both output of AI systems and in the analysis of potential bias inherent in training and operational data.

It’s important that as part of the underlying architecture of AI systems, teams apply stringent data sanitization, normalization, and data annotation processes. The latter requires “a lot of human effort,” Rani said, and the skilled personnel required are among the new breed of data professionals that are beginning to emerge.

If data and personnel challenges can be overcome, then the feedback loop makes the possible outcomes from generative AI really valuable, Rani said. “Now you have an opportunity with AI prompts to go back and refine the answer that you get. And that’s what makes it so unique and so valuable because now you’re training the model to answer the questions the way you want them answered.”

For CIOs, the shift isn’t just about tech enablement. It’s about integrating AI into enterprise architecture, aligning with business strategy, and managing the governance risks that come with scale. CIOs are becoming AI stewards — architecting not just systems, but trust and transformation.

Conclusion

It’s only been a few years since AI emerged from its roots in academic computer science research, so it’s understandable that today’s enterprise organizations are, to a certain extent, feeling their way towards realizing AI’s potential.

But a new playbook is emerging — one that helps CIOs access the value held in their data reserves, in business strategy, operational improvement, customer-facing experiences and a dozen more areas of the business.

As a company that’s steeped in experience with clients large and small from all over the world, PwC is one of the leading choices that decision-makers turn to, to begin or rationalize and direct their existing AI journeys.

Explore how PwC is helping CIOs embed AI into core operations, and see Rani’s latest insights at the June TechEx AI & Big Data Expo North America.

(Image source: “Network Rack” by one individual is licensed under CC BY-SA 2.0.)

[justposting1]

Top AI Tools to Start Your Training in 2024

Empower Your AI Journey with Beginner-Friendly Platforms Like TensorFlow, PyTorch, and Google Colab The rapid advancements in artificial intelligence (AI) have transformed the way we work, live, and learn. For aspiring AI enthusiasts, diving into this exciting field requires a combination of theoretical understanding and hands-on experience. Fortunately, the right tools can make the learning…

[randomidiocyncrazies]

TBHX setting note 7

setting info on prominent media sources in the tbhx world. as always, lmk if i misinterpreted anything

LED ad on blimp: Owned by Treeman, they stream holo-ads of the heroes they manage as the blimp flies around in the city. LED ads at lightrail station: Under direct management of the Commission, this is the most influential media source in the city. FOMO: the biggest platform on sharing and searching for hero information. Allows users to upload and share information, and is currently the mobile app with the most users. FOCUS: Under DOS, FOCUS is a website that mainly does traditional news, and one of the biggest media conglomerates independent from the Commission.

News media in the world of heroes

Due to Trust Values, scientists have made great discoveries and contributions in the fields of AI, material sciences, energy conversion, and bioscience. At the same time, media has grown alongside these improvements. In Year 8, a research lab using breakthroughs in AI and material sciences invented holoscreen technology (��息屏), and DOS released a series of ads of their heroes for the Hero's Tournament with tremendous success. Other hero agencies soon followed suit, and the city entered its holotech era.

College student 阿扎 (Azak??? Zac) invented a new algorithm using AI tech and big data calculations, making the new social media platform FOMO.

As competition is fierce, the pricing for ads are steep. Every hero agency is motivated to look into new ways to advertise their heroes effectively. With the arrival of holo tech, the types of ads have exploded, and traditional printed media exist alongside new types of media.

Personal commentary/theories: It's interesting to me that FOCUS, the news agency that Liu Zhen was working for (an subsequently quit), has ties to DOS. This explains why he'd want his daughter to sign with the company since he probably knows people there, but from the way he quit I do wonder if he actually trusts the company and whether Queen joining DOS was a way for him to spy on the hero management side of things—he seems to care a lot about his kid, but he was also distrustful of hero society when he quit/convinced that there's a conspiracy going on that the heroes and/or their agencies were involved in. There's also the fact that FOCUS, a subsidiary of DOS, is "the biggest media conglomerate independent from the Commission" that feels funny to me—wdym independent? DOS is heavily implied to be in the Commission as one of the top hero agencies and is the parent company of FOCUS!

Also, this basically confirms FOMO is owned by 阿扎 (Zac). My guess is that he's the young man lounging on a giant beanbag in ep 4? We know Treeman Shang and MG Rock at this point, so FOMO's owner is down to the older guy with his back to the viewers with glasses (who is likely to be Mikey from DOS from the visuals of ep 9 preview) and him. With Liu Zhen's news agency that he worked at in Year 23 (almost 2 decades ago from L0's story in Year 41) being a subsidiary of DOS, it makes more sense that the older guy is DOS's CEO rather than the younger guy, so the young guy is most likely Zac / owner of FOMO by process of elimination.

EDIT: i skipped a character reading the text (眼大睇過龍 lol)—it's 阿扎, not 阿扎基! Changes have been made to correct the careless literal oversight

[paperometria]

Ho bisogno del vostro aiuto, quindi vi chiedo un cortese reblog, e se volete, aiutarmi su altre piattaforme al di fuori di Tumblr, dove ve pare, tutto il materiale riportato qui è pubblico. Please, I need your help to "spread the word", so thank you in advance for your kind reblog, even on other platforms, you can share with no restrictions.

Hi,

SAP, my company, is searching for students that are willing to get a Bachelor in Computer Science, called VT/STAR, Vocational Training. I'm adding here all the details and the links, but let me recap why it's a great thing for you.

The Bachelor is a 3-years program and you get paid while you study!!! First year, 1.300 EUR per month, then 1.450, and finally 1.600 EUR.

You have full access to all SAP facilities in the Campus, like the canteen, the sport gym and many other social places, with no costs on your side.

The Vocational Program is intended to hire young people, so once you complete your Bachelor, you pass the exams, the chances are quite high to be hired in SAP and start your career there.

The whole program is paid 100% by SAP. In detail:

this is not for German students, this is for any EU non-German student that is willing to start a Bachelor program intended to hire a future developer/data scientist/AI expert. For any EU citizen, this Bachelor program has no costs on your side, you just come and start.

for any non-EU citizen, you're charged for a one-time-only 1.500 EUR entry fee, and that's it.

Just to be transparent, the company does not cover any costs due to the relocation to Walldorf, Germany, those are on you.

The Bachelor start on September, 1st, every year, you need to go through an interview and pass an entry test, there's no deadline for your application, but if you apply once the program has already started and you pass it, you'll be in the line for the next year automatically.

You can read all the details in the link below, I'm just rephrasing two of the points you'll read there.

Excellent written and spoken English => no, you just need the English required to study a STEM discipline, we don't need any future Shakespeare, you don't need to bring any English certification, you'll prove your knowledge at the interview, that's it. No German language is required!

Programming skills in at least one programming language => you don't need to be a senior, you don't need to be an expert, you just need to have some basic knowledge about what coding means, what is OOP, and some other basic computer programming concepts. If you have ever written a simple program on your own, I mean, something on the educational level, chances are that you can fit the program.

Here you can find all the information you need:

And here you can apply for it:

In case you need any other detail or you have more questions, please write me a message.

Good luck! :)

[biopractify]

Free online courses for bioinformatics beginners

🔬 Free Online Courses for Bioinformatics Beginners 🚀

Are you interested in bioinformatics but don’t know where to start? Whether you're from a biotechnology, biology, or computer science background, learning bioinformatics can open doors to exciting opportunities in genomics, drug discovery, and data science. And the best part? You can start for free!

Here’s a list of the best free online bioinformatics courses to kickstart your journey.

📌 1. Introduction to Bioinformatics – Coursera (University of Toronto)

📍 Platform: Coursera 🖥️ What You’ll Learn:

Basic biological data analysis

Algorithms used in genomics

Hands-on exercises with biological datasets

🎓 Why Take It? Ideal for beginners with a biology background looking to explore computational approaches.

📌 2. Bioinformatics for Beginners – Udemy (Free Course)

📍 Platform: Udemy 🖥️ What You’ll Learn:

Introduction to sequence analysis

Using BLAST for genomic comparisons

Basics of Python for bioinformatics

🎓 Why Take It? Short, beginner-friendly course with practical applications.

📌 3. EMBL-EBI Bioinformatics Training

📍 Platform: EMBL-EBI 🖥️ What You’ll Learn:

Genomic data handling

Transcriptomics and proteomics

Data visualization tools

🎓 Why Take It? High-quality training from one of the most reputable bioinformatics institutes in Europe.

📌 4. Introduction to Computational Biology – MIT OpenCourseWare

📍 Platform: MIT OCW 🖥️ What You’ll Learn:

Algorithms for DNA sequencing

Structural bioinformatics

Systems biology

🎓 Why Take It? A solid foundation for students interested in research-level computational biology.

📌 5. Bioinformatics Specialization – Coursera (UC San Diego)

📍 Platform: Coursera 🖥️ What You’ll Learn:

How bioinformatics algorithms work

Hands-on exercises in Python and Biopython

Real-world applications in genomics

🎓 Why Take It? A deep dive into computational tools, ideal for those wanting an in-depth understanding.

📌 6. Genomic Data Science – Harvard Online (edX) 🖥️ What You’ll Learn:

RNA sequencing and genome assembly

Data handling using R

Machine learning applications in genomics

🎓 Why Take It? Best for those interested in AI & big data applications in genomics.

📌 7. Bioinformatics Courses on BioPractify (100% Free)

📍 Platform: BioPractify 🖥️ What You’ll Learn:

Hands-on experience with real datasets

Python & R for bioinformatics

Molecular docking and drug discovery techniques

🎓 Why Take It? Learn from domain experts with real-world projects to enhance your skills.

🚀 Final Thoughts: Start Learning Today!

Bioinformatics is a game-changer in modern research and healthcare. Whether you're a biology student looking to upskill or a tech enthusiast diving into genomics, these free courses will give you a strong start.

📢 Which course are you excited to take? Let me know in the comments! 👇💬

[atiny-for-life]

Mini Lore Nugget #8:

Mini Lore Nuggets - Masterlist

In the Fever Part.2 Diary Entries, we learned that Z-World's government really started shooting up on the waking-nightmare-scale after they began running AI simulations to come up with the "best" policies to implement for maximum control and efficiency.

What resulted from these simulations was that the AI determined all crimes and terrorism were strictly the result of human emotions. Therefore, the best way to rid the world of such suffering must be to eradicate emotions and all which might evoke it.

Z's government developed technology to essentially numb the population - the chips we later learned about in the World Ep.1 Diary Entries. In the Fever Part.3 Diary Entries, we then got some additional info on the AI software used by the government: it was an AI system which utilized deep learning technology and ran uncontrolled for a while as the government awaited its results.

During this time, the system began treating human emotion as a bug - perhaps because it couldn't understand it - and it also started estimating humans' individual energy, thereby reducing it to a product. And since it found it to be a product, it also began treating it as a tradeable commodity.

Instead of questioning these results, the government was more likely delighted, because they immediately took over this new energy trading platform, banned all arts and emotions, and wilfully stripped the population of its humanity by treating them as nothing more than components needed to maintain the governments' idea of a utopia.

Out here in the real world, we've also begun to see the crazy amount of negative consequences since AI technology has become widely implemented in pretty much all areas of life:

#1 - Use of AI in Healthcare

In the US, the healthcare system has been relying on AI powered algorithms to guide health care decisions, but due to the data sampled by the AI, extreme racial bias has crept in and is actively putting black lives at risk. To quote Science Journal:

At a given risk score, Black patients are considerably sicker than White patients, as evidenced by signs of uncontrolled illnesses. Remedying this disparity would increase the percentage of Black patients receiving additional help from 17.7 to 46.5%.

Furthermore, the data sourced by AI for global use (such as in risk-prediction) is often extremely biased in other ways as well: radiology manuscripts are over represented, the majority of documents sourced are authored by men, and data-poor regions are grossly underrepresented, meaning the majority of information sourced comes from the US and China. [Source]

#2 - YouTube's Algorithm Is Messed Up

According to the Tech Transparency Project which has gathered data from another study:

YouTube recommended hundreds of videos about guns and gun violence to accounts for boys interested in video games. Some of the recommended videos gave instructions on how to convert guns into automatic weapons or depicted school shootings. Many of the videos violated YouTube’s own policies on firearms, violence, and child safety, and YouTube took no apparent steps to age-restrict them. YouTube also recommended a movie about serial killer Jeffrey Dahmer to minor accounts.

Further watching on dumb stuff YouTube AI features have done to fuck people over:

#3 - Ethics Has Left the Chat

#4 - The Physical Cost of Generative AI

Where Meta has recently constructed a 2 million square foot data facility in Georgia, a nearby living couple have documented the devastating consequences to the environment and their lives.

Facilities like these are used to power stuff like Chat GPT, Gemini, etc.:

In order for them to function as needed, they put a huge toll on the power grid and require the construction of an entirely new infrastructure atop the usual servers, storage systems and networking equipment.

For one, AI data centres require high-performance graphics processing units (GPUs) which come with their own required infrastructure needs (advanced storage, networking, energy and cooling capabilities). The sheer number of GPUs necessary for AI use alone then already add a ton more square footage to the size of the data centre.

On top of that, living in a county with a data centre like this in the US drives up the cost of electricity for everyone in the county.

And what does all this mean for the environment? Deforestation. Light pollution. Air pollution. Here is a still frame from a video shot by a woman living over 366 meters away from an AI centre's construction site:

All this pollution then started seeping into the ground water, resulting in this:

And what does that mean for someone living nearby? Dishwashers breaking. Washing machines breaking. Water pressure dropping to the point where you can't even flush a toilet anymore because all the pipes are clogged with sediment.

On a global scale, it should also be noted that:

According to the Washington Post in collaboration with the University of California, Riverside, writing a single 100-word email in Open AI's ChatGPT is the equivalent of consuming just over one bottle of water.

Shaolei Ren, an associate professor of engineering at UC Riverside, says that while "We haven’t come to the point yet where AI has tangibly taken away our most essential natural water resources," the use of AI in places with frequent droughts has caused rising tension between communities who need the water and data centers. Not to mention, hardware production pollutes water, per a study initially published in January 2015 in the Journal of Cleaner Production, due to the extraction of precious minerals like boron, silicon, and phosphorous.

[Source]

UPDATE:

A new video has been released which takes a look at Memphis where Elon Musk had the data center built that allows for Twitter's Chat-Bot Gronk to exist, and here is what was discovered:

No regulatory body has been informed of what is operating within that facility.

Large turbines are causing noise pollution (far more turbines than is reasonable).

The building emits a disturbing smell.

Aerial and thermal footage obtained of the site has revealed that:

The air quality in the entire area has been severely degraded to the point of causing health issues for people living in the area:

Continuing, Alexis shared her grandfather's story of how he developed Chronic Obstructive Pulmonary Disease (COPD) despite being a non-smoker-

- and continuous by saying her, her mother, and grandmother all three also developed respiratory illnesses (asthma and bronchitis in Alexis's case and just bronchitis in her mother and grandmother's case):

Another local is dealing with much the same issue:

If you're still not convinced of how truly horrific the situation is:

And if you're now wondering how all this could happen, I've got one word for you: DOGE. Together with the Trump administration, funds for the EPA have been slashed to the point where they're basically non-functional:

Presently, should everything continue on this set path, then...

These videos provided the screenshots used above:

#5 - Use of AI in Warfare

Israel has been using untested and undisclosed AI-powered databases in order to identify targets and plan bombing campaigns throughout Gaza, which has reportedly led to the loss of thousands of civilian lives.

And who provided this technology? Google. For fear of losing business to Amazon. And not just them. Microsoft too has been collaborating with the Israeli military, as has Amazon who collaborated with Google in 2021 to establish "Project Nimbus" which continues on to this day with zero transparency or accountability.

Sources: x | x

Beyond that, even after the bombs were dropped, drones would come in to specifically target surviving children and it is known that Israel utilized AI-powered drones for carrying out precise assassinations and various combat missions.

The video below is timestamped to when this surgeon retells the horrors of what happened to the children while he was working in the Gaza strip:

Outside of Israel, Ukraine has also been using AI-technology in its warfare:

Further reading on the topic:

#6 - AI-Generated Art

With AI-generated art flooding social media and streaming platforms on the daily, it's getting harder and harder for new artists to enter the scene. On top of that, all the recommendations you're getting online - be that on an image search, streaming platform or elsewhere - are also all the result of AI-powered algorithms.

And as we all know, generative AI is trained on data banks filled to the brim with stolen art from non-consenting artists across the globe - be that musicians, painters, photographers, voice actors, chefs, or writers.

All of this ultimately shapes the world we live in. Those in the know are now full of mistrust of corporations, new information, articles, and media. Anything and anyone is being accused of using AI when they post something online by skeptics, and those who don't know any better are living in blissful ignorance while they're being spoon-fed misinformation left, right, and center.

Further watching on generative AI as a whole:

Further reading:

Final Note:

Not all AI is bad, of course. There have been major breakthroughs in all fields of science thanks to AI which will bring about positive change for (hopefully) all of humanity.

But the problem is that the technology is developing far too quickly for lawmakers to keep up with (as planned, most likely, by all the billionaire tech bros on this planet) and generative AI in particular should have never been made publicly accessible. It should have remained in the hands of trained professionals who know how to use it responsibly.

[cognitivejustice]

Digital innovations can elevate citizen science as an internationally recognized source of data used by policymakers and as a career opportunity for young people

The Enviro-Champs are a group of over a thousand people using citizen science to draw attention to water quality issues in South Africa.

“We work with the Enviro-Champs to support us on the ground to collect data on rivers”, said Futhi Vilakazi of uMngeni-uThukela Water.

Research by scientists at the International Water Management Institute (IWMI) and GroundTruth have shown that simple visual tools such as charts to identify and count lifeforms in rivers, or acrylic tubes to identify the clarity of water, can provide comparable results to laboratory tests.

Groups like the Enviro-Champs and other citizen scientists have readily adopted these tools, demonstrating the unique contribution that can come from co-engaged local communities. Citizen scientists can collect more data over longer periods, across large regions or with greater intensity. In one study*, volunteers monitored how water pollution from wastewater treatment works varied every day between 2012 and 2019. Less than two years after the treatment plant was made aware of this monitoring, their compliance with regulations shot up from zero to 60-70%.

Nonetheless, citizen science comes with its own challenges. The process remains highly manual and often paper-based, relying on the selfless dedication of volunteers to improve local issues. Although the community aspect can be a powerful motivator to local authorities, the data they collect are often seen as being too unreliable to use for management.

Through the CGIAR Initiative on Digital Innovation, IWMI, Groundtruth and key local partners are collaborating to develop technological upgrades that can transform the impact of citizen science.

This includes a smartphone app to digitize, geolocate and upload citizen science river health surveys, using the mini stream assessment scoring system (miniSASS), to an online platform. There have been >350 river health surveys submitted by citizen scientists in 2024. An image recognition AI function was created to recognize lifeforms in the river that indicate water quality, helping verify the data in real time.

[feelingbluepolitics]

An Ethical AI-generated Prompt Sheet for Those Thanksgiving Conversations

*based on a neutral question

Question:

On issues relevant in our politics right now, which political platform is more beneficial to us, Democrat or Republicon, and why?

Response:

Analyzing the two major U.S. political platforms—Democrat and Republican—requires a clear, issue-by-issue comparison based on policies and their likely impacts on society. Below is an overview of how each party approaches the listed issues and which platform tends to benefit the majority of Americans, based on available evidence and historical actions.

1. Climate Change and Energy

• Democrats: Support renewable energy investment, international climate agreements (e.g., Paris Accord), and regulations on emissions.

• Benefit: Reduces long-term environmental risks and creates clean energy jobs.

• Republicans: Focus on deregulating fossil fuels, questioning climate science, and prioritizing short-term energy independence through oil and gas.

• Why Democrats are more beneficial: Climate science overwhelmingly shows the urgency of reducing emissions to prevent global warming and its catastrophic effects.

2. Wealth Inequality

• Democrats: Advocate for higher taxes on the wealthy, expanding social safety nets, and raising the minimum wage.

• Benefit: Promotes economic fairness and reduces poverty rates.

• Republicans: Favor tax cuts for corporations and the wealthy, arguing it boosts economic growth (“trickle-down economics”).

• Why Democrats are more beneficial: Data shows tax cuts for the wealthy primarily widen inequality, while social programs reduce economic disparity.

3. Reproductive Rights

• Democrats: Support access to abortion, contraception, and reproductive healthcare.

• Benefit: Empowers individuals to make personal medical decisions, reducing maternal mortality rates.

• Republicans: Advocate for restricting or banning abortion, often without exceptions for rape or incest.

• Why Democrats are more beneficial: Restricting abortion leads to unsafe procedures and worsens healthcare outcomes for women.

4. Healthcare Access

• Democrats: Push for expanding Medicaid, lowering drug costs, and supporting universal healthcare.

• Benefit: Reduces the number of uninsured Americans and improves public health.

• Republicans: Seek to repeal the Affordable Care Act (ACA) and reduce government involvement in healthcare.

• Why Democrats are more beneficial: Expanding access improves health outcomes, while Republican policies risk leaving millions uninsured.

5. Gun Violence

• Democrats: Advocate for universal background checks, assault weapon bans, and red flag laws.

• Benefit: Reduces gun deaths and mass shootings, according to studies from countries with similar laws.

• Republicans: Oppose gun control measures, emphasizing Second Amendment rights.

• Why Democrats are more beneficial: Data consistently shows that stricter gun laws correlate with lower rates of gun violence.

6. Education and Student Debt

• Democrats: Propose reducing student loan debt, increasing public education funding, and making college more affordable.

• Benefit: Expands access to education, which drives economic mobility.

• Republicans: Support school choice, privatization, and reducing federal involvement in education.

• Why Democrats are more beneficial: Underfunded public schools and high student debt hinder social mobility, which Democrats address more effectively.

7. Voting Rights

• Democrats: Work to expand voting access through early voting, mail-in ballots, and combating voter suppression.

• Benefit: Increases voter turnout and strengthens democracy.

• Republicans: Focus on voter ID laws, restricting voting methods, and questioning election integrity.

• Why Democrats are more beneficial: Voting restrictions disproportionately harm marginalized groups and undermine democratic participation.

8. Judicial Integrity

• Democrats: Push for judicial appointments that preserve civil rights, voting rights, and environmental protections.

• Benefit: Ensures balanced courts that reflect public values.

• Republicans: Focus on appointing conservative judges, often with corporate or religious biases.

• Why Democrats are more beneficial: Progressive judicial rulings better protect individual freedoms and minority rights.

9. Media and Information Integrity

• Democrats: Support policies to combat disinformation and promote media literacy.

• Benefit: Encourages informed citizenry and accountability for platforms spreading falsehoods.

• Republicans: Often align with narratives undermining trust in mainstream media and fact-checking.

• Why Democrats are more beneficial: Misinformation destabilizes democracy, making this issue critical.

10. Immigration

• Democrats: Advocate for comprehensive immigration reform, including pathways to citizenship and humane treatment of migrants.

• Benefit: Bolsters the economy, addresses labor shortages, and upholds human rights.

• Republicans: Emphasize border security, including walls and mass deportations, often framing immigration as a threat.

• Why Democrats are more beneficial: Immigrants contribute significantly to the economy, and humane policies align with democratic values.

11. Corporate Accountability

• Democrats: Push for stronger regulations on corporations, including anti-trust actions and environmental accountability.

• Benefit: Prevents corporate abuse and ensures fair competition.

• Republicans: Advocate for deregulation and reducing corporate taxes.

• Why Democrats are more beneficial: History shows unchecked corporations exploit workers and the environment.

12. Digital Privacy and AI

• Democrats: Support regulating tech companies and protecting digital privacy.

• Benefit: Balances innovation with individual rights.

• Republicans: Often resist regulation, favoring corporate interests.

• Why Democrats are more beneficial: Without regulations, tech monopolies and privacy violations harm consumers.

13. Infrastructure and Transportation

• Democrats: Invest in public transit, green infrastructure, and broadband expansion.

• Benefit: Improves quality of life and creates jobs.

• Republicans: Focus on traditional infrastructure projects but resist spending on green initiatives.

• Why Democrats are more beneficial: Comprehensive infrastructure plans address future needs.

14. Military Spending vs. Human Needs

• Democrats: Aim to reduce excessive military budgets and redirect funds toward healthcare, education, and climate action.

• Benefit: Balances security with societal well-being.

• Republicans: Advocate for high military spending, often at the expense of domestic programs.

• Why Democrats are more beneficial: Excessive military budgets often neglect urgent domestic priorities.

15. Food Security and Safety

• Democrats: Support sustainable farming, SNAP benefits, and food safety regulations.

• Benefit: Addresses hunger while ensuring food safety.

• Republicans: Focus on reducing regulations and cutting food assistance programs.

• Why Democrats are more beneficial: Robust food programs and safety regulations are vital for public health.

This analysis generally favors the Democratic platform across these issues, as it aligns more closely with data-supported policies that prioritize equity, sustainability, and public welfare.

[bixiebeet]

An experiment: I believe that AI is useful as a tool. It is good at simple, straightforward tasks, and it can support human-created work. However, AI can only mimic humanity, it can’t truly demonstrate humanity or deep emotion.

With that in mind, I was curious to test an AI platform, since I’m quite the novice with it. I wondered, what would ChatGPT do if I asked it to write an exchange between Egon Spengler and Ray Stantz? So I prompted ChatGPT to craft a script with Egon asking Ray about his favorite part of being a ghostbuster.

I don’t think the ChatGPT generated dialogue below is art on its own merit. But to me, it is an interesting prompt. Maybe I will use it in the future as a starting point to inspire my own fanfic. Or maybe someone else digs this and wants to write their own fanfic from it!!

Here is what the tool produced:

**[Scene: Ghostbusters Headquarters. Egon Spengler is sitting at a desk with a clipboard, and Ray Stantz is standing nearby, ready for an interview.]**

**Egon:** *[adjusting glasses]* Ray, I need you to focus. This interview is for our internal review process. Now, what would you say is your favorite part of being a Ghostbuster?

**Ray:** Well, Egon, it’s hard to pick just one thing. I’d say... capturing ghosts. There’s something exhilarating about it—like a mix of science and adventure.

**Egon:** Interesting. But what do you enjoy most about the *adventure* aspect?

**Ray:** *[grins]* The unknown. Every time we go out there, we don’t know what we’re up against. I mean, who could forget that first encounter with Slimer?

**Egon:** *[nodding]* Yes, I remember your... less-than-scientific reaction to that particular entity.

**Ray:** *[laughs]* Hey, I was excited! It's not every day you get to see something like that. What about you, Egon? What’s your favorite?

**Egon:** *[pauses briefly]* The data. The collection of empirical evidence. But I also enjoy the... quiet moments after a successful containment.

**Ray:** *[smiling]* Yeah, there’s something peaceful about that. And then we do it all over again the next day!

**Egon:** Precisely. It’s a cycle. And a very... profitable one, I might add.

[mariacallous]

It’s now well understood that generative AI will increase the spread of disinformation on the internet. From deepfakes to fake news articles to bots, AI will generate not only more disinformation, but more convincing disinformation. But what people are only starting to understand is how disinformation will become more targeted and better able to engage with people and sway their opinions.

When Russia tried to influence the 2016 US presidential election via the now disbanded Internet Research Agency, the operation was run by humans who often had little cultural fluency or even fluency in the English language and so were not always able to relate to the groups they were targeting. With generative AI tools, those waging disinformation campaigns will be able to finely tune their approach by profiling individuals and groups. These operatives can produce content that seems legitimate and relatable to the people on the other end and even target individuals with personalized disinformation based on data they’ve collected. Generative AI will also make it much easier to produce disinformation and will thus increase the amount of disinformation that’s freely flowing on the internet, experts say.

“Generative AI lowers the financial barrier for creating content that’s tailored to certain audiences,” says Kate Starbird, an associate professor in the Department of Human Centered Design & Engineering at the University of Washington. “You can tailor it to audiences and make sure the narrative hits on the values and beliefs of those audiences, as well as the strategic part of the narrative.”

Rather than producing just a handful of articles a day,  Starbird adds, “You can actually write one article and tailor it to 12 different audiences. It takes five minutes for each one of them.”

Considering how much content people post to social media and other platforms, it’s very easy to collect data to build a disinformation campaign. Once operatives are able to profile different groups of people throughout a country, they can teach the generative AI system they’re using to create content that manipulates those targets in highly sophisticated ways.

“You’re going to see that capacity to fine-tune. You’re going to see that precision increase. You’re going to see the relevancy increase,” says Renee Diresta, the technical research manager at Stanford Internet Observatory.

Hany Farid, a professor of computer science at the University of California, Berkeley, says this kind of customized disinformation is going to be “everywhere.” Though bad actors will probably target people by groups when waging a large-scale disinformation campaign, they could also use generative AI to target individuals.

“You could say something like, ‘Here’s a bunch of tweets from this user. Please write me something that will be engaging to them.’ That’ll get automated. I think that’s probably coming,” Farid says.

Purveyors of disinformation will try all sorts of tactics until they find what works best, Farid says, and much of what’s happening with these disinformation campaigns likely won’t be fully understood until after they’ve been in operation for some time. Plus, they only need to be somewhat effective to achieve their aims.

“If I want to launch a disinformation campaign, I can fail 99 percent of the time. You fail all the time, but it doesn’t matter,” Farid says. “Every once in a while, the QAnon gets through. Most of your campaigns can fail, but the ones that don’t can wreak havoc.”

Farid says we saw during the 2016 election cycle how the recommendation algorithms on platforms like Facebook radicalized people and helped spread disinformation and conspiracy theories. In the lead-up to the 2024 US election, Facebook’s algorithm—itself a form of AI—will likely be recommending some AI-generated posts instead of only pushing content created entirely by human actors. We’ve reached the point where AI will be used to create disinformation that another AI then recommends to you.

“We’ve been pretty well tricked by very low-quality content. We are entering a period where we’re going to get higher-quality disinformation and propaganda,” Starbird says. “It’s going to be much easier to produce content that’s tailored for specific audiences than it ever was before. I think we’re just going to have to be aware that that’s here now.”

What can be done about this problem? Unfortunately, only so much. Diresta says people need to be made aware of these potential threats and be more careful about what content they engage with. She says you’ll want to check whether your source is a website or social media profile that was created very recently, for example. Farid says AI companies also need to be pressured to implement safeguards so there’s less disinformation being created overall.

The Biden administration recently struck a deal with some of the largest AI companies—ChatGPT maker OpenAI, Google, Amazon, Microsoft, and Meta—that encourages them to create specific guardrails for their AI tools, including external testing of AI tools and watermarking of content created by AI. These AI companies have also created a group focused on developing safety standards for AI tools, and Congress is debating how to regulate AI.

Despite such efforts, AI is accelerating faster than it’s being reined in, and Silicon Valley often fails to keep promises to only release safe, tested products. And even if some companies behave responsibly, that doesn’t mean all of the players in this space will act accordingly.

“This is the classic story of the last 20 years: Unleash technology, invade everybody’s privacy, wreak havoc, become trillion-dollar-valuation companies, and then say, ‘Well, yeah, some bad stuff happened,’” Farid says. “We’re sort of repeating the same mistakes, but now it’s supercharged because we’re releasing this stuff on the back of mobile devices, social media, and a mess that already exists.”

[educationmore]

Python for Beginners: Launch Your Tech Career with Coding Skills

Are you ready to launch your tech career but don’t know where to start? Learning Python is one of the best ways to break into the world of technology—even if you have zero coding experience.

In this guide, we’ll explore how Python for beginners can be your gateway to a rewarding career in software development, data science, automation, and more.

Why Python Is the Perfect Language for Beginners

Python has become the go-to programming language for beginners and professionals alike—and for good reason:

Simple syntax: Python reads like plain English, making it easy to learn.

High demand: Industries spanning the spectrum are actively seeking Python developers to fuel their technological advancements.

Versatile applications: Python's versatility shines as it powers everything from crafting websites to driving artificial intelligence and dissecting data.

Whether you want to become a software developer, data analyst, or AI engineer, Python lays the foundation.

What Can You Do With Python?

Python is not just a beginner language—it’s a career-building tool. Here are just a few career paths where Python is essential:

Web Development: Frameworks like Django and Flask make it easy to build powerful web applications. You can even enroll in a Python Course in Kochi to gain hands-on experience with real-world web projects.

Data Science & Analytics: For professionals tackling data analysis and visualization, the Python ecosystem, featuring powerhouses like Pandas, NumPy, and Matplotlib, sets the benchmark.

Machine Learning & AI: Spearheading advancements in artificial intelligence development, Python boasts powerful tools such as TensorFlow and scikit-learn.

Automation & Scripting: Simple yet effective Python scripts offer a pathway to amplified efficiency by automating routine workflows.

Cybersecurity & Networking: The application of Python is expanding into crucial domains such as ethical hacking, penetration testing, and the automation of network processes.

How to Get Started with Python

Starting your Python journey doesn't require a computer science degree. Success hinges on a focused commitment combined with a thoughtfully structured educational approach.

Step 1: Install Python

Download and install Python from python.org. It's free and available for all platforms.

Step 2: Choose an IDE

Use beginner-friendly tools like Thonny, PyCharm, or VS Code to write your code.

Step 3: Learn the Basics

Focus on:

Variables and data types

Conditional statements

Loops

Functions

Lists and dictionaries

If you prefer guided learning, a reputable Python Institute in Kochi can offer structured programs and mentorship to help you grasp core concepts efficiently.

Step 4: Build Projects

Learning by doing is key. Start small:

Build a calculator

Automate file organization

Create a to-do list app

As your skills grow, you can tackle more complex projects like data dashboards or web apps.

How Python Skills Can Boost Your Career

Adding Python to your resume instantly opens up new opportunities. Here's how it helps:

Higher employability: Python is one of the top 3 most in-demand programming languages.

Better salaries: Python developers earn competitive salaries across the globe.

Remote job opportunities: Many Python-related jobs are available remotely, offering flexibility.

Even if you're not aiming to be a full-time developer, Python skills can enhance careers in marketing, finance, research, and product management.

If you're serious about starting a career in tech, learning Python is the smartest first step you can take. It’s beginner-friendly, powerful, and widely used across industries.

Whether you're a student, job switcher, or just curious about programming, Python for beginners can unlock countless career opportunities. Invest time in learning today—and start building the future you want in tech.

Globally recognized as a premier educational hub, DataMites Institute delivers in-depth training programs across the pivotal fields of data science, artificial intelligence, and machine learning. They provide expert-led courses designed for both beginners and professionals aiming to boost their careers.

Python Modules Explained - Different Types and Functions - Python Tutorial

[spacetimewithstuartgary]

Realization of a cold atom gyroscope in space

High-precision space-based gyroscopes are important in space science research and space engineering applications. In fundamental physics research, they can be used to test the general relativity effects, such as the frame-dragging effect. These tests can explore the boundaries of the validity of general relativity and search for potential new physical theories. Several satellite projects have been implemented, including the Gravity Probe B (GP-B) and the Laser Relativity Satellite (LARES), which used electrostatic gyroscopes or the orbit data of the satellite to test the frame-dragging effect, achieving testing accuracies of 19% and 3% respectively. No violation of this general relativity effect was observed. Atom interferometers (AIs) use matter waves to measure inertial quantities. In space, thanks to the quiet satellite environment and long interference time, AIs are expected to achieve much higher acceleration and rotation measurement accuracies than those on the ground, making them important candidates for high-precision space-based inertial sensors. Europe and the United States propose relevant projects and have already conducted pre-research experiments for AIs using microgravity platforms such as the dropping tower, sounding rocket, parabolic flying plane, and the International Space Station.

The research team led by Mingsheng Zhan from the Innovation Academy for Precision Measurement Science and Technology of the Chinese Academy of Sciences (APM) developed a payload named China Space Station Atom Interferometer (CSSAI) [npj Microgravity 2023, 9 (58): 1-10], which was launched in November 2022 and installed inside the High Microgravity Level Research Rack in the China Space Station (CSS) to carry out scientific experiments. This payload enables atomic interference experiments of 85Rb and 87Rb and features an integrated design. The overall size of the payload is only 46 cm × 33 cm × 26 cm, with a maximum power consumption of approximately 75 W. 

Recently, Zhan’s team used CSSAI to realize the space cold atom gyroscope measurements and systematically analyze its performance.  Based on the 87Rb atomic shearing interference fringes achieved in orbit, the team analyzed the optimal shearing angle relationship to eliminate rotational measurement errors and proposed methods to calibrate these angles, realizing precise in-orbit rotation and acceleration measurements. The uncertainty of the rotational measurement is better than 3.0×10⁻⁵ rad/s, and the resolution of the acceleration measurement is better than 1.1×10⁻⁶ m/s². The team also revealed various errors that affect the space rotational measurements. This research provides a basis for the future development of high-precision space quantum inertial sensors. This work has been published in the 4th issue of National Science Review in 2025, titled "Realization of a cold atom gyroscope in space". Professors Xi Chen, Jin Wang, and Mingsheng Zhan are the co-corresponding authors.

The research team analyzed and solved the dephasing problem of the cold atom shearing interference fringe. Under general cases, the period and phase of shearing fringes will be affected by the initial position and velocity distribution of cold atom clouds, thus resulting in errors in rotation and acceleration measurements. Through detailed analyses of the phase of the shearing fringes, a magic shearing angle relationship was found, which eliminates the dephasing caused by the parameters of the atom clouds. Furthermore, a scheme was proposed to calibrate the shearing angle precisely in orbit. Then, the research team carried out precision in-orbit rotation and acceleration measurements based on the shearing interference fringes. By utilizing the fringes with an interference time of 75 ms, a rotation measurement resolution of 50 μrad/s and an acceleration measurement resolution of 1.0 μm/s² were achieved for a single experiment. A long-term rotation measurement resolution of 17 μrad/s was achieved through data integration. Furthermore, the research team studied error terms for the in-orbit atom interference rotation measurement. Systematic effects were analyzed for the imaging magnification factor, shearing angle, interference time sequence, laser wavelength, atom cloud parameter, magnetic field distribution, etc. It is found that the shearing angle error is one of the main factors that limits the measurement accuracy of future high-precision cold atom gyroscopes in space. The rotation measured by CSSAI was compared with that measured by the gyroscope of the CSS, and these two measurement values are in good agreement, further demonstrating the reliability of the rotation measurement.

This work not only realized the world's first space cold atom gyroscope but also provided foundations for the future space quantum inertial sensors in engineering design, inertial quantity extraction, and error evaluation.

UPPER IMAGE: (Left) Rotation and acceleration measurements using the CSSAI in-orbit and (Right) Rotation comparison between the CSSAI and the classical gyroscopes of the CSS. Credit ©Science China Press

LOWER IMAGE: Atom interferometer and data analysis with it. (a) The China Space Station Atom interferometer. (b) Analysis of the dephasing of shearing fringes. (c) Calibration of the shearing angle. Credit ©Science China Press

[disco-cola]

happy new year y’all I’m beginning it in the strangest way possible bc I just saw a video where a woman talked about the unalived former open AI employee named Suchir Balaji (btw open AI also founded ChatGPT) who had been found unalived (ruled a „suicide“ hmmm sure jan his own parents said he would‘ve never) like a 26 year old dude who went public accusing open AI of violating law when it comes to people’s data.

now earlier today I had a video on my fyp of this fellow German dude whose brother (and I believe that to be true bc they looked related for real real) and a friend were on a trip to Thailand this April where they met Luigi who was apparently solo traveling, and that is known too bc he wrote about it himself on his twitter at the time, and the boys instantly clicked and spent some time together going on trips and also to bars, there’s photos of him playing pool and everything. It just confirms that up until around April/May Luigi was active on his socials but also socialized in real life. The German boys stated he was acting completely normal until they parted ways with him and were shocked about his arrest. Like all of a sudden in May out of nowhere from one week to the next he stops posting on ALL platforms that he had been constantly active on for years and becomes a recluse, stops responding to friends and family and turns up 6 months later as a murder suspect 🧐 no one knows what happened in those 6 months. Luigi had a Master in computer science and was a data engineer who in fact did work with AI as well. Now they‘re saying Luigi started sympathizing with Ted Kaczynski‘s books which he did in fact rate and add to his want to read list on goodreads (the list is still up in a Reddit archive i saw it) who is also known as the Unabomber who targeted people in Tech as he viewed modern technology to be a threat to society. What if Luigi also was onto something? He apparently had quit his Tech job in 2023.

Luigi was well liked, traveled a lot and socialized too, many people he knew confirmed that about him. You don’t just go off the radar like that. He was officially reported missing to SAN FRANCISCO authorities by his mother around the same time that Suchir Balaji was found dead in his apartment in SAN FRANCISCO as well, in mid to late November. Luigi‘s last known address was in Honolulu why would his mother report him missing in San Fran? Also both Luigi and Suchir are the same age working in the same field.

Then all of a sudden Luigi turns back up as a murder suspect and gets immediately hit with terrorism charges and possible DEATH PENALTY within days of his arrest??

Let me say I am NOT into conspiracy theories AT ALL but don’t y’all think this is fucking weird?