The predictive power of Artificial Intelligence (AI) has proven itself and its value is no longer under scrutiny. This should explain why the AI adoption has been so prevalent in recent years. The technology has been applied to many use cases such as finance (determine which applicant gets a loan), medicine (making sense of X-Rays, ECG scans, and making sense of Electronic Medical Records), understanding human speech (smart speakers such as Alexa), movie and book recommendation engines used by the likes of Netflix, Amazon and others. The list goes on and on. Truthfully it is probably easier to keep track…


Seeking Help from Artificial Intelligence

Introduction

Having been involved in the field of Artificial Intelligence (AI) for years, I can attest that becoming proficient in this field is not an easy undertaking. The complexity stems from its multi- dimensionality. In other words, gaining competence in AI requires competencies in math, statistics, computer programming, cloud computing, among others. Despite its complexity, the fundamental concept behind AI is very simple. …


Five years ago, there was no integrated circuit (IC) product category called “Deep Learning Processors”. Training and inference of large Artificial Intelligence (AI) models was primarily done by high-end servers and Graphics Processing Units (GPU).

What a change can five years make.

Presently there are no fewer than 20 major semiconductor fabless/IDM companies that offer AI chips. They range from giants such as AMD, Nvidia, Intel, Qualcomm, to smaller pure-play vendors such as Graphcore, Cerebras, Groq, Gyrfalcon, Hailo among many others. Building AI inference and training chips has not been exclusive to chip vendors. …


AI-Based Object Detection and Text Extraction Technologies Have Revolutionized the Document Processing Domain

The short answer to the posed question in the title is “a lot”.

To set the stage for this article, I would like start with an example. Consider being tasked to analyze the scanned version of a company annual report (form 10-k). The document typically contains various types of fields such as pure text, form (name, position, and compensation of officers), tables (e.g. income statement, balance sheet), and even images. Just extracting the textual characters from the document is not nearly enough to conduct any meaningful analysis…


Developing, training, and deploying deep learning models are non-trivial and time consuming. Having the right tools can make a huge difference

Machine Learning is a diverse field covering a wide territory and has impacted many verticals. It is able to tackle tasks in language and image processing, anomaly detection, credit scoring sentiment analysis, forecasting alongside dozens of other downstream tasks. A proficient developer, in this line of work; has to be able to draw, borrow, and steal from many adjacent fields such as mathematics, statistics, programming, and most importantly common sense. I for one have drawn tremendous benefits from myriad of tools available to break down complex tasks into smaller more manageable components. It turns out that developing and training a…


Clearly last week’s most notable events in the world of AI were the NeurIPS conference held in Vancouver (see the segment below) as well as the acquisition of Habana Labs (Israeli Deep Learning hardware company) by Intel for $2B.

As for Natural Language Processing (NLP), more and more industries are finding great use cases that can benefit from NLP. I have included blurbs on a few upstarts that leverage NLP doing great things for the healthcare industry.

The domination of transformer-based language models is expanding and we are seeing smaller and more efficient implementations of the BERT — Bidirectional Encoder…


The overarching objective of this newsletter is to highlight key Deep Learning technological developments and innovations that impact the underlying hardware, including accelerator chips, IP, accelerator cards, tools, memory, and systems.

  1. Intel debut “Ice Lake” processor intended for laptops. This is the first processor based on 10nm process technology and supports sizable deep learning capabilities thanks to 64 GPU execution engines. Separately Intel unveiled high-performance PAC D5005 accelerator PCIe card for compute-intensive applications in data centers such as AI inference, media transcoding, and streaming analytics. …

Al Gharakhanian

Passionate about Machine Learning

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store