#Data Science Support

[great-and-small]

Yet another scientific article adding to the slowly growing mountain of evidence that suggests we might be able to save the world through bird-watching.

[aro-culture-is]

quick note - this blog is gonna be sparse again for at least this week. trying new medications and tbh initial side effects are not super pleasant + actual effects build up. as a result: currently as if unmedicated for mental health, with anxiety+ side effect, extra fatigue, dizziness, and fatigue. it's uh, sure something.

totally recognize that most of y'all know we're absent at times due to health things, just wanted to give a heads up that this one is at least anticipated.

[the-awesomecosmos-studies]

Feb 19, 2024

Day 1 of 100 days of productivity. Went to a local cafe, worked on the data cleaning for my side project in RStudio, got an iced coffee and poppyseed cake slice. Sent some emails, polished an old blog article and posted it. 7/10 productive vibes today.

[jimin-nothing-stronger]

I’ve long joked that Python is a slightly demonic programming language, but I just realized — Python, like the serpent of Eden! Python, like Crowley!

Anyway, my new headcanon is that Python is one of Crowley’s demonic innovations, designed to generate low-level discontent and petty bitterness among programmers and scientists around the globe. I cannot be convinced otherwise. (This is possibly the only way I can trick myself into actually appreciating its serpentine wiles.)

[venusianplums]

Aella

when i grow up i wanna be just like her

[artykyn]

Me: I’m going back to school and switching careers to programming

My coworkers who I had for 8 months: Oh :/ such a shame that you’re leaving tissue culture :/ it’s so hard to find people with good TC skills :/ why programming though?? So random

My previous boss at a TC company who I worked with for 4.5 years and who I still keep in touch with: Yeah that tracks. You’ll be great at that.

[jcmarchi]

3 Questions: Should we label AI systems like we do prescription drugs?

New Post has been published on https://thedigitalinsider.com/3-questions-should-we-label-ai-systems-like-we-do-prescription-drugs/

3 Questions: Should we label AI systems like we do prescription drugs?

AI systems are increasingly being deployed in safety-critical health care situations. Yet these models sometimes hallucinate incorrect information, make biased predictions, or fail for unexpected reasons, which could have serious consequences for patients and clinicians.

In a commentary article published today in Nature Computational Science, MIT Associate Professor Marzyeh Ghassemi and Boston University Associate Professor Elaine Nsoesie argue that, to mitigate these potential harms, AI systems should be accompanied by responsible-use labels, similar to U.S. Food and Drug Administration-mandated labels placed on prescription medications.

MIT News spoke with Ghassemi about the need for such labels, the information they should convey, and how labeling procedures could be implemented.

Q: Why do we need responsible use labels for AI systems in health care settings?

A: In a health setting, we have an interesting situation where doctors often rely on technology or treatments  that are not fully understood. Sometimes this lack of understanding is fundamental — the mechanism behind acetaminophen for instance — but other times this is just a limit of specialization. We don’t expect clinicians to know how to service an MRI machine, for instance. Instead, we have certification systems through the FDA or other federal agencies, that certify the use of a medical device or drug in a specific setting.

Importantly, medical devices also have service contracts — a technician from the manufacturer will fix your MRI machine if it is miscalibrated. For approved drugs, there are postmarket surveillance and reporting systems so that adverse effects or events can be addressed, for instance if a lot of people taking a drug seem to be developing a condition or allergy.

Models and algorithms, whether they incorporate AI or not, skirt a lot of these approval and long-term monitoring processes, and that is something we need to be wary of. Many prior studies have shown that predictive models need more careful evaluation and monitoring. With more recent generative AI specifically, we cite work that has demonstrated generation is not guaranteed to be appropriate, robust, or unbiased. Because we don’t have the same level of surveillance on model predictions or generation, it would be even more difficult to catch a model’s problematic responses. The generative models being used by hospitals right now could be biased. Having use labels is one way of ensuring that models don’t automate biases that are learned from human practitioners or miscalibrated clinical decision support scores of the past.      

Q: Your article describes several components of a responsible use label for AI, following the FDA approach for creating prescription labels, including approved usage, ingredients, potential side effects, etc. What core information should these labels convey?

A: The things a label should make obvious are time, place, and manner of a model’s intended use. For instance, the user should know that models were trained at a specific time with data from a specific time point. For instance, does it include data that did or did not include the Covid-19 pandemic? There were very different health practices during Covid that could impact the data. This is why we advocate for the model “ingredients” and “completed studies” to be disclosed.

For place, we know from prior research that models trained in one location tend to have worse performance when moved to another location. Knowing where the data were from and how a model was optimized within that population can help to ensure that users are aware of “potential side effects,” any “warnings and precautions,” and “adverse reactions.”

With a model trained to predict one outcome, knowing the time and place of training could help you make intelligent judgements about deployment. But many generative models are incredibly flexible and can be used for many tasks. Here, time and place may not be as informative, and more explicit direction about “conditions of labeling” and “approved usage” versus “unapproved usage” come into play. If a developer has evaluated a generative model for reading a patient’s clinical notes and generating prospective billing codes, they can disclose that it has bias toward overbilling for specific conditions or underrecognizing others. A user wouldn’t want to use this same generative model to decide who gets a referral to a specialist, even though they could. This flexibility is why we advocate for additional details on the manner in which models should be used.

In general, we advocate that you should train the best model you can, using the tools available to you. But even then, there should be a lot of disclosure. No model is going to be perfect. As a society, we now understand that no pill is perfect — there is always some risk. We should have the same understanding of AI models. Any model — with or without AI — is limited. It may be giving you realistic, well-trained, forecasts of potential futures, but take that with whatever grain of salt is appropriate.

Q: If AI labels were to be implemented, who would do the labeling and how would labels be regulated and enforced?

A: If you don’t intend for your model to be used in practice, then the disclosures you would make for a high-quality research publication are sufficient. But once you intend your model to be deployed in a human-facing setting, developers and deployers should do an initial labeling, based on some of the established frameworks. There should be a validation of these claims prior to deployment; in a safety-critical setting like health care, many agencies of the Department of Health and Human Services could be involved.

For model developers, I think that knowing you will need to label the limitations of a system induces more careful consideration of the process itself. If I know that at some point I am going to have to disclose the population upon which a model was trained, I would not want to disclose that it was trained only on dialogue from male chatbot users, for instance.

Thinking about things like who the data are collected on, over what time period, what the sample size was, and how you decided what data to include or exclude, can open your mind up to potential problems at deployment. 

[reviewsdimisco]

Unleashing the Power: Exploring High-Performance Desktops for Gaming

Hey gamers! Are you ready to take your gaming experience to the next level? Today, we're diving into the exhilarating world of high-performance desktops, where raw power meets cutting-edge technology to deliver an unparalleled gaming experience.

Raw Power: High-performance desktops are the juggernauts of the gaming world. With top-of-the-line processors, graphics cards, and RAM, these machines are built to handle the most demanding games with ease. Whether you're exploring vast open worlds, engaging in intense multiplayer battles, or diving into virtual reality realms, a high-performance desktop ensures smooth gameplay and stunning visuals every step of the way.

Customization: One of the most exciting aspects of high-performance desktops is the ability to customize your rig to suit your gaming preferences. From choosing the perfect combination of components to fine-tuning overclocking settings, the possibilities are endless. Whether you're a competitive esports player looking for lightning-fast response times or a graphics enthusiast craving eye-popping visuals, a customized desktop allows you to tailor your gaming experience exactly to your liking.

Future-Proofing: Investing in a high-performance desktop isn't just about the here and now – it's also about future-proofing your gaming setup for years to come. With support for the latest technologies and room for upgrades, these machines are designed to stay ahead of the curve. Whether it's next-gen graphics cards, faster storage options, or innovative cooling solutions, a high-performance desktop ensures that you'll always be ready to tackle the latest games and hardware advancements.

Community and Support: Joining the high-performance desktop community opens up a world of support and camaraderie. Whether you're seeking advice on building your own rig, troubleshooting technical issues, or simply sharing your latest gaming achievements, there's a vibrant community of fellow enthusiasts ready to lend a helping hand. From online forums to local meetups, connecting with other gamers can enhance your gaming experience and provide valuable insights into maximizing the potential of your desktop.

The Ultimate Gaming Experience: At the end of the day, it's all about the gaming experience – and high-performance desktops deliver in spades. Whether you're immersing yourself in a cinematic single-player adventure or competing in intense multiplayer showdowns, the combination of raw power, customization options, future-proofing, and community support culminates in the ultimate gaming experience.

So, if you're ready to unleash the power and elevate your gaming experience to new heights, it's time to explore the world of high-performance desktops. Whether you're a seasoned veteran or a newcomer to the gaming scene, there's never been a better time to dive in and experience gaming like never before. Let the adventure begin! 🎮💻 #Gaming #HighPerformance #Desktops #UnleashThePower

More...

[flaskoflethe]

Well this might dox me. But Microsoft, go fuck yourself. This YOU ARE CLAIMING YOU PARTNER WITH OpenAI TO "Ensure that artificial general intelligence (AGI) benefits humanity". Can't post screenshots (work...) but it's literally on the slides. Genuinely fucking floored this is disgusting

[scholarnest]

Business Intelligence Solutions: Unleashing the Power of Managed Analytics

In today's dynamic business landscape, the effective utilization of data is pivotal for informed decision-making and sustained growth. Business Intelligence (BI) solutions have emerged as a cornerstone, offering organizations the ability to glean actionable insights from their data. This article explores the transformative impact of BI solutions and how managed analytics, coupled with outsourced IT management, is reshaping the way businesses harness the power of data.

1. Proactive IT Support and Managed IT Services:

BI solutions thrive in an environment supported by proactive IT services. Managed IT services, which include proactive support and maintenance, ensure the seamless operation of BI tools. This proactive approach not only enhances the reliability of analytics but also minimizes downtime, allowing businesses to make real-time decisions.

2. Advanced Analytics and Data Visualization Services:

Managed analytics encompass advanced analytics services that go beyond basic reporting. Data visualization services play a crucial role, translating complex data sets into visually appealing and understandable insights. This facilitates better communication and comprehension of data-driven findings across all levels of an organization.

3. Cloud Management Solutions and Migration Strategies:

The integration of cloud management solutions is a game-changer for BI. Cloud migration solutions offer scalability, flexibility, and cost-efficiency. Managed BI services leverage cloud optimization solutions, ensuring that businesses make the most of cloud resources while maintaining peak performance.

4. Data Science Solutions and Hybrid Cloud Integration:

BI solutions often involve intricate data science methodologies. Managed analytics extend to data science solutions, enabling organizations to employ predictive analytics and machine learning for more accurate forecasting. Hybrid cloud solutions provide the necessary infrastructure for hosting and processing data across different environments securely.

5. IT Consultation Services and Strategic Managed Services:

Strategic IT consultation services are instrumental in aligning BI strategies with overall business objectives. Managed services, including serverless computing and big data consulting, are designed to optimize the performance of BI tools, ensuring they adapt to evolving business requirements.

6. Cloud Consulting Services and Holistic Cloud Management:

BI solutions benefit from specialized cloud consulting services. These services guide organizations in selecting the most suitable cloud platforms and architectures for their BI needs. Holistic cloud management services oversee the entire cloud ecosystem, ensuring optimal performance and security.

In conclusion, the convergence of BI solutions and managed analytics is reshaping the way businesses interpret and leverage their data. With the right blend of outsourced IT management, advanced analytics, and cloud solutions, organizations can unlock the full potential of their data, gaining a competitive edge in today's data-driven era.

[marketxcel]

Data-Driven Decision-Making: The Backbone of Successful U.S. Business Strategies

Explore the transformative impact of data-driven decision-making on businesses in the United States. Uncover key insights and strategies that propel success, driving innovation and resilience in today's dynamic market landscape.

[tiredeyes1975]

trying to talk to my mom abt college and shes kinda giving me advice but i dont think she gets my problem…

[nasa]

25 Years of Exploring the Universe with NASA's Chandra Xray Observatory

Illustration of the Chandra telescope in orbit around Earth. Credit: NASA/CXC & J. Vaughan

On July 23, 1999, the space shuttle Columbia launched into orbit carrying NASA’s Chandra X-ray Observatory. August 26 marked 25 years since Chandra released its first images.

These were the first of more than 25,000 observations Chandra has taken. This year, as NASA celebrates the 25th anniversary of this telescope and the incredible data it has provided, we’re taking a peek at some of its most memorable moments.

About the Spacecraft

The Chandra telescope system uses four specialized mirrors to observe X-ray emissions across the universe. X-rays that strike a “regular” mirror head on will be absorbed, so Chandra’s mirrors are shaped like barrels and precisely constructed. The rest of the spacecraft system provides the support structure and environment necessary for the telescope and the science instruments to work as an observatory. To provide motion to the observatory, Chandra has two different sets of thrusters. To control the temperatures of critical components, Chandra's thermal control system consists of a cooling radiator, insulators, heaters, and thermostats. Chandra's electrical power comes from its solar arrays.

Learn more about the spacecraft's components that were developed and tested at NASA’s Marshall Space Flight Center in Huntsville, Alabama. Fun fact: If the state of Colorado were as smooth as the surface of the Chandra X-ray Observatory mirrors, Pike's Peak would be less than an inch tall.

Engineers in the X-ray Calibration Facility at NASA’s Marshall Space Flight Center in Huntsville, Alabama, integrating the Chandra X-ray Observatory’s High-Resolution Camera with the mirror assembly, in this photo taken March 16, 1997. Credit: NASA

Launch

When space shuttle Columbia launched on July 23, 1999, Chandra was the heaviest and largest payload ever launched by the shuttle. Under the command of Col. Eileen Collins, Columbia lifted off the launch pad at NASA’s Kennedy Space Center in Florida. Chandra was deployed on the mission’s first day.

Reflected in the waters, space shuttle Columbia rockets into the night sky from Launch Pad 39-B on mission STS-93 from Kennedy Space Center. Credit: NASA

First Light Images

Just 34 days after launch, extraordinary first images from our Chandra X-ray Observatory were released. The image of supernova remnant Cassiopeia A traces the aftermath of a gigantic stellar explosion in such captivating detail that scientists can see evidence of what is likely the neutron star.

“We see the collision of the debris from the exploded star with the matter around it, we see shock waves rushing into interstellar space at millions of miles per hour,” said Harvey Tananbaum, founding Director of the Chandra X-ray Center at the Smithsonian Astrophysical Observatory.

Cassiopeia A is the remnant of a star that exploded about 300 years ago. The X-ray image shows an expanding shell of hot gas produced by the explosion colored in bright orange and yellows. Credit: NASA/CXC/SAO

A New Look at the Universe

NASA released 25 never-before-seen views to celebrate the telescopes 25th anniversary. This collection contains different types of objects in space and includes a new look at Cassiopeia A. Here the supernova remnant is seen with a quarter-century worth of Chandra observations (blue) plus recent views from NASA’s James Webb Space Telescope (grey and gold).

This image features deep data of the Cassiopeia A supernova, an expanding ball of matter and energy ejected from an exploding star in blues, greys and golds. The Cassiopeia A supernova remnant has been observed for over 2 million seconds since the start of Chandra’s mission in 1999 and has also recently been viewed by the James Webb Space Telescope. Credit: NASA/CXC/SAO

Can You Hear Me Now?

In 2020, experts at the Chandra X-ray Center/Smithsonian Astrophysical Observatory (SAO) and SYSTEM Sounds began the first ongoing, sustained effort at NASA to “sonify” (turn into sound) astronomical data. Data from NASA observatories such as Chandra, the Hubble Space Telescope, and the James Webb Space Telescope, has been translated into frequencies that can be heard by the human ear.

SAO Research shows that sonifications help many types of learners – especially those who are low-vision or blind -- engage with and enjoy astronomical data more.

Click to watch the “Listen to the Universe” documentary on NASA+ that explores our sonification work: Listen to the Universe | NASA+

An image of the striking croissant-shaped planetary nebula called the Cat’s Eye, with data from the Chandra X-ray Observatory and Hubble Space Telescope.  NASA’s Data sonification from Chandra, Hubble and/or Webb telecopes allows us to hear data of cosmic objects. Credit: NASA/CXO/SAO

Celebrate With Us!

Dedicated teams of engineers, designers, test technicians, and analysts at Marshall Space Flight Center in Huntsville, Alabama, are celebrating with partners at the Chandra X-ray Center and elsewhere outside and across the agency for the 25th anniversary of the Chandra X-ray Observatory. Their hard work keeps the spacecraft flying, enabling Chandra’s ongoing studies of black holes, supernovae, dark matter, and more.

Chandra will continue its mission to deepen our understanding of the origin and evolution of the cosmos, helping all of us explore the Universe.

The Chandra Xray Observatory, the longest cargo ever carried to space aboard the space shuttle, is shown in Columbia’s payload bay. This photo of the payload bay with its doors open was taken just before Chandra was tilted upward for release and deployed on July 23, 1999. Credit: NASA

Make sure to follow us on Tumblr for your regular dose of space: http://nasa.tumblr.com

[the-awesomecosmos-studies]

Day 5/100 days of productivity | Fri 23 Feb, 2024

Had a great Friday! Started the day with a Dunkin run and got my emotional support iced coffee and stuffed bagel minis to bring forth a productive day (and it worked hehe).

Got put onto an exciting new project at work, yay!

Wrote lots of code at work for my other projects

Met with my professional working women group friend and talked about data science careers, life, grad school, and the new Netflix Avatar series (we’re both too scared to watch it because it might not be as good as the original)

Reorganized my entire Google Calendar

Planned my side projects and productive tasks for the weekend

[astarions-wife]

Ranking Baldur’s Gate 3 Characters/Companions on if they’d be successful in helping you lace a corset.

Astarion: 11/10. He wears them himself, he probably even judges you on how you’re doing it wrong. He has it down to a science.

Shadowheart: 7/10. She wears that corset top to bed. She’s all for the use and style, but she prefers the ones without laces. Probably could do it, but with practice.

Minsc: 5/10. He says “Why do our QUEENS wear these things…” he doesn’t get it. But if asked to help lace a corset, it’s not that he couldn’t—it’s just he’d probably ask Boo to do it.

Lae’zel: 8/10 on skill, because she definitely can, but why would she? She’d click her tongue and call you weak for needing assistance.

Wyll: 10/10, he studies it to be a gentleman. He knows the correct tensions, how hard to pull, how to tie them, etc. he even knows the front lace ones.

Karlach: 6/10. Once the heat is cooled down enough so that she can touch you, I think she’s just so excited to have physical contact with anyone that she forgets the task at hand. She’d have to be reminded frequently.

Jaheira: 9/10, but in a practical way. Like she helps you lace them, while expressing concern about how tight they are, and focuses on doing it right to be supportive and practical for combat.

Gale: 2/10. Don’t get me wrong, he does it right. But he definitely has some kind of spell to do it for him. Now taking it off? That’s a 10/10, a proper science.

Aylin: 12/10, laces Isobel’s corset while proclaiming her love for her. It’s an art form, and Aylin has conquered it.

Isobel: No data. Hasn’t laced a corset since Aylin came back.

Halsin: 7/10, he definitely knows how! I just think he goes off about the “oak father” and how corsets are against natures very way as he’s doing it.

Orin: 0/10, would she even need to? She snaps her fingers to change forms. She wears human flesh on her body. She’d cut a corset off, and then probably you in the process.

Gortash: -2/10. The man can’t even lace his own shirt, let alone someone’s corset.