Traversaal AI

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.@DrJimFan is a senior AI scientist at @nvidia and his work is centered around the development of autonomous agents that are capable of general tasks. His talk today was about how LLM-powered #AI agents are already beginning to master games like Minecraft #TEDAI2023

@_hasanc , Hello Hassan, Are you looking to be introduced to any thought leader in LLM/ AI? I can introduce you to some professors at Stanford/UCLA and also to the founder of the largest/ oldest data science course provider.

How knowledge graphs improve generative AI Large language models have immense potential, but also major shortcomings. Knowledge graphs make LLMs more accurate, transparent, and explainable. infoworld.com/article/370781… W/ @TEDAI2023

.@lucasmearian Hello Lucas, I saw your article about LLMs and AI and I am wondering if you might be open to speaking with two thought leaders in the space from #Stanford and at #UCLA. Please let me know, they can share data & use cases, and lots of objective insight.

The versatility & human-like text-generation abilities of large language models are reshaping how we interact with tech from #Chatbots and #ContentCreation to translation & summarization. harness the benefits of large language models.

This is a great re-cap/ crash course on the foundations of Large Language Models #LLLMs. Really value the in-depth reflection and analysis. lnkd.in/ehXkYCa2

Systems thinking is considered an essential tool for unleashing the full potential of emerging technologies. Who is going to #TEDAI? We can't wait to meet you! forbes.com/sites/forbeste…

@USTglobal @hyro_ai Well done!

We’re excited to partner with @Hyro_AI to bring conversational #AI to our digital transformation solutions for #healthcare. Hyro & UST’s joint offering will enable the redesign of contact centers by simplifying routine tasks & streamlining workflows. bit.ly/3PJ4B8x

Customer experience, business expansion driving conversational AI investment. vietnamnews.vn/economy/159458…

A new study reveals an “AI placebo effect”: the same chatbot will respond differently depending on its users’ assumptions about artificial intelligence. scientificamerican.com/article/the-as…

Embark on a journey through the Chain of Thoughts in AI! 🤯 Discover how AI models link ideas and insights seamlessly. Witness the evolution of conversational AI. #AI #ChainOfThoughts 💭 #AIInnovation #LLMS

@xambao Hi, are you accepting any more speakers, panelists or workshop hosts? Our CEO teaches LLMs and Conversational AI at Stanford and at UCLA.

LMSYS-Chat-1M: A Breakthrough Resource Unveiling the Conversational Power of Large Language Models #AI #AItechnology #artificialintelligence #benchmarkquestions #Contentmoderation #dataset #instructionalfinetuning #llm #LLMs #LMSYSChat1M multiplatform.ai/lmsys-chat-1m-…

🚀What does a Googler do after leaving Google? At traversaal.ai, we're not just following in the footsteps of giants; we're blazing our own trail. Our journey is about innovation, about pushing boundaries, and about creating solutions that transform business ops.

Common Probability Distributions That Occur In Nature And Why Mathematics Is The Language Of The Universe Fundamentally the patterns of the universe repeat themselves making machine learning and AI possible. Basically, when training ML models, including NNs we are attempting to model the patterns in the data. A good model can predict unseen data points that are part of the original data distribution. Here are the common probability distributions and where they occur naturally Symmetry and normal distributions - Nature loves balance. You see it in butterfly wings, faces, and even in physical laws. Natural phenomena that exhibit symmetry often fit well with a normal distribution. The Central Limit Theorem tells us that the sum of many independent, identically distributed variables approaches a normal distribution. These distributions are characterized by a mean and a standard deviation and everything from human heights, IQ scores, and even the velocities of molecules in a gas follow a normal distribution Log-normal distribution - If the logarithm of the variable follows a normal distribution, then the variable itself has a log-normal distribution. The distribution of financial assets, or the sizes of particles generated by grinding, blood pressure, and metabolic rates in various organisms often follow a log-normal distribution. The Log-Normal Distribution often arises from multiplicative growth processes, where you're repeatedly multiplying by some random factor. Uniform Distribution. This is self-explanatory. All outcomes are equally likely. In the continuous case, the probability density function is flat between the minimum and maximum values. Rolling a fair die, or picking a card from a well-shuffled deck follows uniform distributions Poisson Distribution It describes the probability of a given number of events occurring in a fixed interval of time or space. The events must occur with a known constant mean rate and independently of each other. It is the go-to for predicting rare events. Poisson distribution models the number of times a radioactive atom decays in a given time period, or the number of cars passing through a certain point in a given time frame. If a particular intersection sees an average of 10 cars passing through it per minute, the Poisson Distribution can estimate the probability of 15 cars passing through in the next minute. Similarly in sports like hockey or soccer where goals are rare, you can use distribution to model the number of goals scored by each team. Bernoulli Distribution, the binary star of the probability universe! Scientifically speaking, it's a discrete probability distribution that models a single experiment with exactly two outcomes, often termed "success" and "failure," and is characterized by a single parameter p, the probability of success. The flip of a coin, genetic inheritance (you either have a trait or you don't), and the polarization of a single photon (either vertical or horizontal) model this distribution. Binomial Distribution It describes the number of successes in a fixed number of independent Bernoulli trials, each with the same probability of success. For example, The number of heads when flipping a coin multiple times, or the number of defective items in a batch of manufactured goods can be modeled with this distribution. Exponential Distribution models the time you have to wait for the next event in scenarios where events happen independently and at a constant average rate. It's often used to describe phenomena like the time between bus arrivals or the intervals between radioactive decay events. In essence, it's the go-to distribution for understanding "waiting times" in various natural and man-made systems. This is a summary of the most common distributions. There are a bunch of other distributions that are related or variations on the above distributions and the image below captures some of them. These naturally occurring distributions speak to why mathematics is the language of the universe and how you can use it to model and predict its behavior

We’re thrilled to welcome author, comedian and magician Robert Strong to #TEDAI2023! Deemed our new CMO (Chief Magic Officer), this jack of all trades is sure to amaze and delight - much like the wonders of #AI🪄 Grab your ticket before it disappears: go.ted.com/TEDAI23

Mindset is crucial for leadership. Great leaders like Steve Jobs, Elon Musk, and Martin Luther King were distinguished not by their resources but by their mindset. A leader's ability to navigate challenges and opportunities is largely influenced by their mindset. The mindset determines how one deals with situations instantaneously. The brain functions like a neural net, and it's trained by repeated exposure to certain types of information. Constant exposure to negative news can train the brain to be in a state of fear. Throughout my years, I've encountered 7 mindsets that distinguish leaders from followers. These are the Abundance Mindset, Gratitude Mindset, Exponential Mindset, Moonshot Mindset, Longevity Mindset, Curiosity Mindset, and Purpose-Driven Mindset. Do you have any mindsets you've discovered along the way that put you in the right place to succeed?

In 2017, @RichardSocher predicted that #AI would make it easier to fulfill basic human needs by automating processes like farming. Six years later he’s joining us at #TEDAI2023. Want to hear if his predictions have changed? Join us in SF 10/17 & 10/18: go.ted.com/TEDAI23

Voice in retailing. It's about conversational AI integrated into the decision journey and throughout the value chain. It's also -- today -- about tangible, measurable value. readwrite.com/walmarts-secre…