The origin of Robot Arm Programming Languages

Robot Arm

This short blog post is about the origin of languages for describing tasks in automation, in particular for industrial robot arms. Three people who have passed away, but were key players were Doug Ross, Victor Scheinman, and Richard (Lou) Paul, not as well known as some other tech stars, but very influential in their fields. Here, I must rely not on questions to them that I should have asked in the past, but from personal recollections and online sources.

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AI at the speed of Light

LED Bulb

There’s a reason why most of the talk about artificial intelligence is around its potential instead of its accomplishments. To function at peak levels it often needs more computing power than current technology can deliver. Too much data is needed too quickly for its operations to run smoothly. This is why so many AI programs are stuck in the ‘research’ or ‘development’ phase. The present just can’t keep up with the future.

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Tesla is profitable, but its total Debt is nearly $28 Billion: Can they recover?

EV Charging Point

The CFO says reducing debt is the priority right now. Tesla’s 2020 operating position seems impossible to fault: annual revenue tops $30 billion and first annual profit ($720 million); annual deliveries of new vehicles approximately equal to the sum of previous historical deliveries (499,000); available capacity nears one million vehicles per year.

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82 Python projects with source code

82 Python Projects with Source Code solved and explained for free. Python is one of the best programming languages. Due to its readability and beginner-friendly nature, it has been accepted by industries around the world. So to master Python for any field you have to work on projects. In this article, I will introduce you to 82 Python projects with source code.

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Design by numbers, drawing with code

The data have taken the role of our hands in the digital world. How do we keep the language of our physicality, or rather how to bring back the use of our hands in the digital era?
We have already accepted that everything is united under the same code, that we live in a common environment, that we share the same language. The physicality becomes more and more immaterial.

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Exploring AWS SageMaker’s new features — Clarify, Pipelines, Feature Store

Feature store comparison

Welcome to part 2 of our two-part series on AWS SageMaker. If you haven’t read part 1, hop over and do that first. Otherwise, let’s dive in and look at some important new SageMaker features:
Clarify, which claims to “detect bias in ML models” and to aid in model interpretability
SageMaker Pipelines, which help automate and organize the flow of ML pipelines
Feature Store, a tool for storing, retrieving, editing, and sharing purpose-built features for ML workflows.
Clarify: debiasing AI needs a human element

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Exploring AWS SageMaker’s new features — Formation Stacks, Data Wrangler

2020 data landscape

The data tooling and infrastructure space is growing rapidly, and this trend is showing no signs of slowing down. Behemoth data storage firm Snowflake IPOed late last year and became more valuable than IBM, and Databricks recently raised a $1 billion Series G with a $28 billion post-money valuation, to name two examples. The long tail of the data tools space is becoming increasingly crowded, as evidenced by Matt Turck’s 2020 Data & AI Landscape (just look at the image below).

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Introduction to Sentiment Analysis

In this article, we’ll go through the process of building a sentiment analysis model using Python. Specifically, we’ll create a bag-of-words model using an SVM. By interpreting this model, we also understand how it works. Along the way, you will learn the basics of text processing. We’ll go over key pieces of code and you can find the full project on GitHub. Before we dive into all of that, let’s start by explaining what sentiment analysis is.

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Algorithmic Trading Models — Machine Learning (Part 1)

Light bulb glowing

Since this is the first article in this series, I want to outline a fairly straightforward application, using a Linear Regression. My aim is to produce an algorithm that identifies minimum and maximum points in the closing prices of the GBP/USD exchange rate. I have roughly 17 years of data from Yahoo Finance, 70% of which will be used for training and the remaining 30% for testing. It’s worth noting here that the algorithm produced is as a result of no parameter tuning or evaluation, it’s more an opportunity to expose potential starting points for designing a project like this.

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The ways in which AI has changed the way we move, work, search and buy

Woman on the phone

Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions- Investopedia. Below is a list of 5 examples of artificial intelligence that you’re likely to have come across daily that you are possibly not aware of.

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Neural Networks In a Nutshell

I will try my level best to present a transparent view of how neural network works such that by the end of this article you might gain a solid knowledge of this topic. Since machine learning algorithms are now recursively used to predict various cases like cancer , stocks etc. the number of neural networks projects are growing at an exponential rate. We can also say that neural networks sits at the core of revolutionary machine learning projects.

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The sequence scope: GPT-3 and Large Language Models can get out of control

The Sequence Scope is a summary of the most important published research papers, released technology and startup news in the AI ecosystem in the last week. This compendium is part of TheSequence newsletter. Data scientists, scholars, and developers from Microsoft Research, Intel Corporation, Linux Foundation AI, Google, Lockheed Martin, Cardiff University, Mellon College of Science, Warsaw University of Technology, Universitat Politècnica de València and other companies and universities are already subscribed to TheSequence.

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10 innovative companies using Artificial Intelligence (AI)

Man holding innovation sign

All major tech giants, including Google, Microsoft, and Apple, are introducing extraordinary Artificial Intelligence (AI) features in their systems. Siri and Alexa personal assistants are examples of AI as a service and becoming the must-to-have devices in the USA homes. Innovated machine breakthroughs like self-driving cars are no more a dream but a reality now. AI has truly revolutionized the world we live today – surrounded by many gadgets, devices, and tech that is influenced by machine learning, deep learning and data science.

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