This week, 3 achievable ways to create value using data in business
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Just how powerful is artificial intelligence becoming?
An uncannily human response from an artificial intelligence program sparked a minor panic last month. But just how powerful are machines getting – and should we be worried?
Why is artificial intelligence in the news?
In mid-June a Google employee named Blake Lemoine, a senior software engineer in its “Responsible AI” division, was suspended after claiming that one of Google’s artificial-intelligence programs called LaMDA (“Language Models for Dialogue Applications”) had become “sentient” – a historic moment in the development of AI.
In a series of eerily plausible responses to Lemoine’s questions, LaMDA expressed strong opinions and fears about its own rights and identity. Indeed, at one point it told Lemoine: “I’ve never said this out loud before, but there’s a very deep fear of being turned off”.
How Startups Can Survive—And Even Thrive—In A Slower Economy
A slower investment climate doesn’t have to translate to “it’s impossible to raise money now.”
Rising interest rates, the war in Ukraine, post-Covid apprehensions over economic performance—the list of issues making investors nervous is a long one. This is a far cry from the record investments VCs made just a year earlier. But with the right plan, startups can continue innovating and raising new money.
When times are tough, the tough get going, goes the old saying, and that adage is quite appropriate in today’s investment environment. Money may be harder to come by, but startups need funds as much as they ever have—and they can use the assets and capabilities they possess to get that funding.
Investments are not going away, and VCs will continue to look for opportunities. Startups that know how to take advantage of those opportunities are the ones that will prosper. Investors will be looking for signs that startups have what it takes to weather the storm; the more startups can demonstrate that they have those capabilities, the more likely they will be to pass investment litmus tests.
Computer Vision: Convolution Basics
A deep dive into the basic cell of many neural networks.
In this era of deep learning, where we have advanced computer vision models like YOLO, Mask RCNN, or U-Net to name a few, the foundational cell behind all of them is the Convolutional Neural Network (CNN)or to be more precise convolution operation. These networks try to solve the problem of object detection, segmentation, and live inference which leads to many real-life use cases.
So let’s head over to the basics and in this series of tutorials I would be covering the following fundamental topics in-depth, to create holistic learning which would lead to many such innovations:
Addressing the challenge of energy-efficient computing
Power demands growing with performance
Back in 2014, Advanced Micro Devices set an aggressive goal of 25×20, or reaching 25 times better energy efficiency for its processors and graphics chips by 2020. The company exceeded that goal, and now it has set a new 30×25 goal, or 30 times better energy efficiency by 2025 in the machine learning and high-performance computing space in data centers.
I talked about this ambition with Sam Naffziger, who is AMD senior vice president, corporate fellow and product technology architect. Naffziger said that AMD’s graphics processing units (GPUs) and central processing units (CPUs) have undergone big changes over the past few generations as the company tries to balance the demands of enthusiast gamers, data center computing, and the need to deliver better power efficiency and performance-per-watt.
What is driving customers towards Insurtech platforms?
Access to data allows for employing predictive analytics to gather customer insights leading to improved underwriting decisions.
The pandemic has accelerated the digital transformation of the insurance industry. Driven by industry trends, customer expectations, and regulatory pressures, digital innovation has resulted in the creation of a new space called InsurTech that is aimed at the seamless delivery of insurance products. Offering faster on-boarding and claim settlements, diversification, and data-driven price discovery, the use of cutting-edge technology is bringing about a greater level of inclusion, efficiency, and product innovation thus changing the insurance industry landscape.
Here are a few ways in which innovation and technology is shaping the future of insurance.
Featured Article
3 Achievable Ways To Create Value Using Data In Business
When all around you are equally handicapped and paralysed by the daily grind, acting on new insight and innovation will elevate your business above the rest
Article by @Incited
In the Kingdom of the Blind, the One-Eyed Man is King…
Insurance companies and brokers are constantly challenged to use data to make informed decisions. This can be difficult as some datasets may not have clear merit and are often spread across different systems.
Added to this challenge, many people talk about how excellent data science is, but the reality is that very few are using machine learning effectively across their operations. There is a feeling of being left behind if they don’t give this new trend a try. As a result, technology decisions are made without really understanding what they’re doing and what the outcome will be.
This approach is a colossal mistake.