🔮 Tesla AI Day & Why it Sucked 🛃 🖲ðŸ”
And other top AI stories of the week
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The curtains went off at ‘Tesla AI Day 2021’, and lo and behold; there comes a person disguised as a humanoid robot dancing to the tunes of Elon Musk. The entire event was live-streamed for a little more than three hours. The first 50 minutes are dedicated to brilliant music, good sound effects, and the Tesla AV running on the road.
The following 60 to 70 minutes explain the tech behind the Tesla FSD system, Dojo supercomputer, D1 chip, and the idea of a humanoid robot. Unfortunately, the deliverables have gone for a toss amid the hype created around the Tesla AI event.
As anticipated, Tesla’s AI Day incorporated company engineers explaining the upcoming Tesla tech while focusing on attracting and recruiting the brightest to join Tesla’s AI team.
Tesla has unveiled this Dojo supercomputer for the first time at the AI Day even though Elon Musk has been talking it up on Twitter for almost a year now. Tesla has claimed this to be the world’s fastest computer for training ML algorithms.
This is not the first time Musk has made tall claims. There have been several instances in the past when he promised to deliver but has failed.
1
The Ugly Side Of No Code AI Platforms
Codex and Copilot are powered by GPT-3, which is trained on a publicly available dataset. This also means that the code generated is more of a probabilistic exercise of finding the best code. This can usher bad code into the systems.
The researchers at NYU fear that the model will not necessarily generate the best code but rather the one that best matches the code that came before. According to the researchers, the quality of the generated code can be strongly influenced by semantically irrelevant features of the prompt.
2
How Dream Sports Uses Artificial Intelligence
Founded in 2008, by Harsh Jain and Bhavit Sheth, Dream Sports is a sports technology company with brands such as Dream 11, FanCode, DreamX, and DreamSetGo.
In a recent conversation with Analytics India Magazine(AIM), Amit Sharma, Chief Technology Officer of Dream Sports explained how the sports technology company is leveraging artificial intelligence(AI) and machine learning(ML) technologies to better its product and services delivery for users.
3
Can We Teach Machines To Think Twice?
Last week, Deepmind introduced PonderNet, a new algorithm that allows artificial neural networks to learn to think for a while before answering. Halting to think is something very familiar to humans.
In machines, the target is always to pick the most optimised route in less time using lesser compute. This new model by DeepMind answers a more fundamental problem by introducing halting steps into the model.
4
Data Science Hiring Process At Ather Energy
Ather Energy has about 10 data scientists who work with edge devices and cloud development, feature deployment, and analysis of the vast data it collects. The company’s data science team is divided into two streams — vehicle intelligence and web intelligence.
At Ather Energy, the data science teams solve a wide gamut of problems. The changes are rapid.
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Webinar Recording: Do You Think You Can Analytics?
The webinar was hosted by Navin Dhananjaya, Chief Solutions Officer at Ugam, a Merkle company. Witnessing the growing demand, Ugam recently announced plans to hire over 1,300 analytics and technology professionals in India.
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Hands-on Guides for ML Developers
+ LSTM Vs GRU in Recurrent Neural Network: A Comparative Study
+ Beginner's Guide To Transfer Learning - How and When to Use?
+ Understanding Direct Domain Adaptation in Deep Learning
+ How to Visualize a Random Forest with Fitted Parameters?
+ All You Need To Know About PyTorch’s New PipeTransformer
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PEOPLE & STARTUPS
+ The Machine Learning Journey Of Aishwarya Srinivasan
+ Interview With Sriram Srinivasan, Technical Lead At Google
+ How This Fintech Startup Uses ML To Disburse Loans And Detect Fraud
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Risks Of Using Foundational Models Such As GPT-3
Google’s foundational model BERT powers the search engine used by billions across the world. OpenAI’s GPT-3 is a powerful language model that has forayed into downstream tasks such as building low code platforms.
In the era of such large scale foundational models that directly impact many real-world applications, what are the risks that tag along?
9
The Rise & Rise Of Postman
Postman has emerged as the most valued Indian SaaS startup. In its latest Series D funding round, Postman raised $225 million, taking its overall valuation to $5.6 billion. The financing round was led by New York-based Insight Partners, with participation from other investors, including Nexus Venture Partners, CRV, BOND, Battery Ventures, etc.
So what explains Postman’s increasing popularity?
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BOTTOM OF THE NEWS
Here's what all happened last week.
+ Punjab Govt & IIT Ropar Offer Free Courses In AI And Data Science
+ IIT Madras & IBM Collaborate For Programming And Data Science Course
+ NVIDIA Announces General Availability Of NVIDIA AI Enterprise
+ Deep Tech Startup Tooliqa Innovations Raises $1.5M Pre-seed Funding
+ Agritech Robotics Startup TartanSense Raises $5 Million In Series A
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