Olzhas Baibulganov’s Post

Sharing a great article about 2024 compensation benchmarks. I am happy to schedule a conversation to discuss our current employment market. Feel free to reach out to me at Janea@willmott.com

Rabies at interface between wildlife, livestock and humans is one of the largely neglected hotspots. Looking into knowledge, attitudes and practices contiguous to wildlife reserves is paramount prior to rabies prevention intereventions are employed. We developed a knowledge conceptual quadrant for rabies transmission and prevention which policy makers and other researchers can start from, improve or evaluate appropriately. We are glad to publish and share this paper. https://lnkd.in/dRVa9fpM

Check out our new blog: https://lnkd.in/eFjWt2cY Do you know nothing? Here's an argument against the possibility of knowledge

Use the link below to read the article! https://lnkd.in/gmYFFwdj

New on the blog! 🖤 Read the full article here: https://lnkd.in/g2j8JHDC

Learn from the best – Read; The Best of the Best This Year – Plus an Analysis of Why They did so Well - https://ow.ly/VtMT50TksGZ

Using this study case – https://lnkd.in/dpGnGtkS

This is indeed a problem that is old - I know it since 25 years ... - and it does not only hit AI development, it has made life difficult for any developer of intelligent solutions for the energy sector - also those that work with traditional intelligence (meaning physics...) 🤔 ! Time has run out ⌛ to keep on talking - we need to hit the start button to change the situation instead - NOW! Technology is no longer a hindrance, it's policy and mindset that are the barriers today! Let's work together as a community and let our collaboration be driven by the hunger for data, investigate what the "open minded" do in e.g. in Australia, where all energy data is accessible down to wind farm of solar park level, and COLLABORATE instead of compete on data! In the #IEAWind #Task51, we have startet collaboration with the #IEC and #WMO to built a standard for forecasting -> which in large is a standard for "data handling" for forecasting!   Forecasts can only be developed, improved and made intelligent by using trustworthy and valid observational data -- from meteorological data to power output of renewables, as well as demand, we all sit in the same boat! We can learn a lot from the meteorological community and how the GTS network works, but without an international umbrella such as the #IEA, we just continue to all brew our own little soup.... So, I also want to invite "anybody-with-this-problem" or "anybody-sitting-with-data-that-could-be-shared-but-is-not" to get in touch with us here on LinkedIN 👉 https://lnkd.in/d2-A7Wbb , or via our home page 👉 https://lnkd.in/eFqJkiXF and 👉 meet us at one of our next events, and get involved in our workstream "Data Science and AI" (https://lnkd.in/dB3eC7At) ... we will also have a webinar series end of the year 👉 get in touch with us to open a broad discussion on data accessibility in the energy sector.  Together we will be 💪 enough to move this topic forward!

Thought + experiment – can text on a screen respond to the distance it is being viewed from? Documentation here: https://lnkd.in/dNg8jWSr

This article synchs perfectly with my 2024. https://lnkd.in/gJTEHkNc