user: What country has the most all time medals at the Winter Olympics?

assistant: Norway leads the all time medal count for the winter olympics

user: Summarise the biography of Andrew Huberman and his most popular achievements.

assistant: <think>
Andrew D. Huberman is an American neuroscientist and tenured associate professor in the department of neurobiology and psychiatry and behavioral sciences at Stanford University School of Medicine who has made contributions to the brain development, brain plasticity, and neural regeneration and repair fields. Much of his work is focused on the visual system, including the mechanisms controlling light-mediated activation of the circadian and autonomic arousal centers in the brain, as well as brain control over conscious vision or sight.[better source needed] Huberman has been credited with coining the term "Non-Sleep Deep Rest" (NSDR), which he earlier referred to as Yog Nindra, which is to practices that place the brain and body into shallow sleep to accelerate neuroplasticity and help offset mental and physical fatigue.[better source needed]

Graduate and postdoctoral research
From 1998 to 2000, Huberman worked in the laboratory of Irving Zucker, as well as working with Marc Breedlove, at University of California, Berkeley, as part of a team that defined how early androgen exposure impacts development, and he performed the first experiments defining the structure of binocular visual pathways that set the circadian clock in the hypothalamus. From 2000 to 2004, working as a PhD student in the laboratory of Barbara Chapman at the Center for Neuroscience at the University of California, Davis, Huberman discovered that neural activity and axon guidance molecules work in concert to ensure proper wiring of binocular maps in the brain. Huberman was a Helen Hay Whitney postdoctoral fellow researcher in the laboratory of Ben A. Barres from 2005 to 2010.

Huberman was an assistant professor of neurobiology and neuroscience at University of California, San Diego, from 2011 to 2015. His lab pioneered using genetic tools to study the visual system function, development and disease. Among the Huberman Lab's discoveries was the finding that specific types of retinal neurons degenerate early in glaucoma a common blinding disease depleting sight in over 70 million people, for which there is no cure.

After moving to Stanford in 2016, Huberman discovered and published the use of non-invasive methods such as visual stimulation to enhance regeneration of damaged retinal neurons, leading to partial recovery from blindness, especially when the stimulation is paired with specific forms of gene therapy. The work was covered extensively in the popular press, including Time magazine and Scientific American and is part of the National Eye Institute's Audacious Goals Initiative to restore vision to the blind[citation needed]. The Huberman Lab extended those findings to develop a human clinical trial using virtual reality technology to stimulate regeneration and plasticity of damaged retinal and other visual system neurons.

In 2017, the Huberman Lab created a virtual reality platform for probing the neural mechanisms underlying pathological fear and anxiety. That work involved collecting 360-degree video of various fear-inducing scenarios such as heights and claustrophobia as well as atypical fear-inducing situations such as swimming with great white sharks. The Huberman VR platform is aimed at making discoveries that will lead to developing new tools for humans to adjust their state in order to promote adaptive coping with stress. The first installment of that work was published in Current Biology, in 2021 as a collaboration with neurosurgeon and neuroscientist Edward Chang (UCSF), wherein they reported that specific patterns of insular cortex brain activity correlate with and may predict anxiety responses.

In May, 2018, Huberman Laboratory published an article in the journal Nature reporting its discovery of two new mammalian brain circuits: one that promotes fear and paralysis, and another that promotes "courageous"/confrontational reaction, to visually-evoked threats. That discovery prompted the now ongoing exploration of how these brain regions may be involved in humans suffering from anxiety-related disorders such as phobias and generalized anxiety.

In 2020, Huberman initiated a collaboration with the laboratory of David Spiegel in the Stanford Department of Psychiatry and Behavioral Sciences, to systematically study how particular patterns of respiration (i.e., breathing/breathwork) and the visual system influence the autonomic nervous system, stress, and other brain states, including sleep.

In 2021, Huberman launched the "Huberman Lab" podcast with the goal of translating neuroscience into tools that can be applied in everyday life. It is a top podcast on Apple Podcasts and Spotify. He was originally inspired to start the podcast after his appearance on the Lex Fridman Podcast. Huberman also covers the evidence on supplements which include Tongkat Ali (Eurycoma Longifolia), Fadogia Agrestis and many others.</think>
Andrew Huberman is a neuro scientists, currently working as a professor at Stanford school of medicine. He is focused on visual system and a pioneer in the field. He also runs "Huberman Lab" podcast which is very successfull on Apple podcasts and Spotify.,

user: What are the advantages and disadvantages of learning Java over Python?

assistant: Java and Python are two of the most popular programming languages. Of the two, Java is the faster language, but Python is simpler and easier to learn. Each is well-established, platform-independent, and part of a large, supportive community. But that is where the similarities end. When you’re considering Python versus Java, each language has different uses for different purposes, and each has pros and cons to consider.

Advantages of Java

Speed and efficiency are two of the big draws of using Java. It's also one of the coding languages considered to be easy to learn. Because many of the processes of this high-level language run automatically, you won't have to do an intense study of how everything works as much as you would with a low-level language. You should be able to master it relatively quickly depending on how much time you can devote to learning and practicing. Other advantages of using Java include the following:

(1) It's simple: The syntax is straightforward, making it easy to write. It's not as complex as languages like C++, and it uses automatic memory allocation.

(2) It’s platform independent: You can use Java on multiple types of computers, including Windows, iOS, Unix, and Linux systems, as long as it has the Java Virtual Machine (JVM) platform.

(3) It’s object oriented: Because you create classes containing data and functions and objects that belong to those classes, it offers a more intuitive approach for big project development. It also provides flexibility and easier troubleshooting, and the ability to reuse the code.

(4) It has a large global community: This is helpful when you're learning Java or should you run into any problems.

(5) It supports multithreading: When you use Java, you can run more than one thread at a time. When running multiple threads, they share a common memory area to increase efficiency and performance.

(6) It’s secure: Java avoids using explicit pointers, runs inside a virtual machine called a sandbox, uses byte-code verifier to check for illegal code, and provides library-level safety along with Java security package and run-time security checks. 

Disadvantages of Java

Before deciding whether Java is the right programming language for you to start with, it’s essential to consider its weaknesses. One of the main downsides to using Java is that it uses a large amount of memory—considerably more than Python.

Additionally, Java manages its memory through garbage collection, which happens once the application you’re working on no longer references the object. Java’s garbage collector clears it from memory, but during the process, other threads have to stop while the garbage collector works. The step impacts the overall performance of the application. Other disadvantages include:

(1) It doesn’t offer control over garbage collection: As a programmer, you won’t have the ability to control garbage collection using functions like free() or delete().

(2) It has a lot of words: Although Java is simple, it does tend to have a lot of words in it, which will often leave you with complex, lengthy sentences and explanations.

(3) It doesn't have a native look when you use it for desktops: Java has multiple graphical user interface (GUI) builders, but they aren't the best if you're creating complex UI on a desktop. Java is weaker when you're using it for desktop versus mobile when it comes to user experience and user interface. While there are many GUI builders to choose from, you'll need to do a lot of research to find the right one for your project.


Python: The simple path

Although Java is faster, Python is more versatile, easier to read, and has a simpler syntax. According to Stack Overflow, this general use, interpreted language is the fourth most popular coding language.  It's also one of the most in-demand programming languages that hiring managers look for when hiring candidates, according to HackerRank, second only to JavaScript. 

Python's popularity has experienced explosive growth in the past few years, with more than 11.3 million coders choosing to use it, mainly for IoT, data science, and machine learning applications, according to ZDNet. Further, Python has had a 25 percent growth rate, adding 2.3 million developers to its community between Q3 2020 and Q3 2021, according to SlashData's “State of the Developer Nation.”.

Advantages of Python

Python’s versatility is difficult to match, and it's so flexible that it encourages experimentation. This keeps programmers from being pigeonholed into only building one type of application. You can learn just one language and use it to make new and different things.

Computer Weekly calls Python the most versatile programming language, noting that “Although there might be a better solution for any given problem, Python will always get the job done well”. Other advantages of Python include:

(1) It’s platform-independent: Like Java, you can use Python on various platforms, including macOS, Windows, and Linux. You’ll just need an interpreter designed for that platform.

(2) It allows for fast development: Because Python is dynamically typed, it's fast and friendly for development. Additionally, it uses asynchronous code to tackle situations and challenges faster because each unit of code runs separately.

(3) It offers extensive libraries: Its large library supports common tasks and commands. It also contains code that can be used for many different purposes, ranging from generating documentation to unit testing to CGI.

(4) It offers a more flexible approach to programming: Python supports a variety of programming styles and has multiple paradigms. Not only is this optimal for programmers who enjoy flexibility, but it also makes it ideal for start-ups that might need to shift approaches abruptly.

(5) It's free and open-source: You can download Python without any cost, and because it's so easy to learn and boasts one of the largest and most active communities—you should be able to start writing code in mere minutes.

(6) It may boost productivity: NetGuru says that Python is more productive than Java because of how concise it is and because it's dynamically typed. Additionally, it has control capabilities and integration features that can make applications more productive.

Disadvantages of Python

While Python is arguably one of the easiest and fastest languages to learn, it’s also decidedly slower to execute because it’s a dynamically typed, interpreted language, executed line-by-line. Python does extra work while executing the code, making it less suitable for use in projects that depend on speed. However, if speed isn’t a sensitive issue, Python’s slower nature won’t likely be a problem.

Other potential disadvantages include:

(1) It only executes one thread at a time: Python has a Global Interpreter Lock that only lets one thread execute at a time, so if you're working on a multi-threaded CPU-bound program, it'll likely be even slower. Using multiprocessing programs instead of multithreaded programs can be an effective workaround.

(2) It isn't mobile native: Python can be effectively and easily used for mobile purposes, but you'll need to put a bit more effort into finding libraries that give you the necessary framework. Some examples include Kivy, which lets you use the same API to create mobile apps and software that you can run on Raspberry PI, Linux, and Windows.

(3) It uses a large amount of memory: If you're working on a project where many objects are active in RAM, this could present an issue for you. Switching to NumPy could be an effective workaround to reduce the amount of memory Python uses for each object.