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One of the biggest highlights of Build, Microsoft’s annual software development conference, was the presentation of a tool that uses deep learning to generate source code for office applications. The tool uses GPT-3, a massive language model developed by OpenAI last year and made available to select developers, researchers, and startups in a paid application programming interface.

Many have touted GPT-3 as the next-generation artificial intelligence technology that will usher in a new breed of applications and startups. Since GPT-3’s release, many developers have found interesting and innovative uses for the language model. And several startups have declared that they will be using GPT-3 to build new or augment existing products. But creating a profitable and sustainable business around GPT-3 remains a challenge.

Microsoft’s first GPT-3-powered product provides important hints about the business of large language models and the future of the tech giant’s deepening relation with OpenAI.

A few-shot learning model that must be fine-tuned?

Microsoft uses GPT-3 to translate natural language commands to data queries
Credit: Microsoft Power Apps blog
Microsoft uses GPT-3 to translate natural language commands to data queries

According to the Microsoft Blog, “For instance, the new AI-powered features will allow an employee building an e-commerce app to describe a programming goal using conversational language like ‘find products where the name starts with “kids.”’ A fine-tuned GPT-3 model [emphasis mine] then offers choices for transforming the command into a Microsoft Power Fx formula, the open source programming language of the Power Platform.”

I didn’t find technical details on the fine-tuned version of GPT-3 Microsoft used. But there are generally two reasons you would fine-tune a deep learning model. In the first case, the model doesn’t perform the target task with the desired precision, so you need to fine-tune it by training it on examples for that specific task.

In the second case, your model can perform the intended task, but it is computationally inefficient. GPT-3 is a very large deep learning model with 175 billion parameters, and the costs of running it are huge. Therefore, a smaller version of the model can be optimized to perform the code-generation task with the same accuracy at a fraction of the computational cost. A possible tradeoff will be that the model will perform poorly on other tasks (such as question-answering). But in Microsoft’s case, the penalty will be irrelevant.

In either case, a fine-tuned version of the deep learning model seems to be at odds with the original idea discussed in the GPT-3 paper, aptly titled, “Language Models are Few-Shot Learners.”

Here’s a quote from the paper’s abstract: “Here we show that scaling up language models greatly improves task-agnostic, few-shot performance, sometimes even reaching competitiveness with prior state-of-the-art fine-tuning approaches.” This basically means that, if you build a large enough language model, you will be able to perform many tasks without the need to reconfigure or modify your neural network.

So, what’s the point of the few-shot machine learning model that must be fine-tuned for new tasks? This is where the worlds of scientific research and applied AI collide.

Academic research vs commercial AI

Credit: Ben Dickson

There’s a clear line between academic research and commercial product development. In academic AI research, the goal is to push the boundaries of science. This is exactly what GPT-3 did. OpenAI’s researchers showed that with enough parameters and training data, a single deep learning model could perform several tasks without the need for retraining. And they have tested the model on several popular natural language processing benchmarks.

But in commercial product development, you’re not running against benchmarks such as GLUE and SQuAD. You must solve a specific problem, solve it ten times better than the incumbents, and be able to run it at scale and in a cost-effective manner.

Therefore, if you have a large and expensive deep learning model that can perform ten different tasks at 90 percent accuracy, it’s a great scientific achievement. But when there are already ten lighter neural networks that perform each of those tasks at 99 percent accuracy and a fraction of the price, then your jack-of-all-trades model will not be able to compete in a profit-driven market.

Here’s an interesting quote from Microsoft’s blog that confirms the challenges of applying GPT-3 to real business problems: “This discovery of GPT-3’s vast capabilities exploded the boundaries of what’s possible in natural language learning, said Eric Boyd, Microsoft corporate vice president for Azure AI. But there were still open questions about whether such a large and complex model could be deployed cost-effectively at scale to meet real-world business needs [emphasis mine].”

And those questions were answered with the optimization of the model for that specific task. Since Microsoft wanted to solve a very specific problem, the full GPT-3 model would be an overkill that would waste expensive resources.

Therefore, the plain vanilla GPT-3 is more of a scientific achievement than a reliable platform for product development. But with the right resources and configuration, it can become a valuable tool for market differentiation, which is what Microsoft is doing.

Microsoft’s advantage

In an ideal world, OpenAI would have released its own products and generated revenue to fund its own research. But the truth is, developing a profitable product is much more difficult than releasing a paid API service, even if your company’s CEO is Sam Altman, the former President of Y Combinator and a product development legend.

And this is why OpenAI enrolled the help of Microsoft, a decision that will have long-term implications for the AI research lab. In July 2019, Microsoft made a $1 billion investment in OpenAI—with some strings attached.

From the OpenAI blog post that declared the Microsoft investment: “OpenAI is producing a sequence of increasingly powerful AI technologies, which requires a lot of capital for computational power. The most obvious way to cover costs is to build a product, but that would mean changing our focus [emphasis mine]. Instead, we intend to license some of our pre-AGI technologies, with Microsoft becoming our preferred partner for commercializing them.”

Alone, OpenAI would have a hard time finding a way to enter an existing market or create a new market for GPT-3.

On the other hand, Microsoft already has the pieces required to shortcut OpenAI’s path to profitability. Microsoft owns Azure, the second-largest cloud infrastructure, and it is in a suitable position to subsidize the costs of training and running OpenAI’s deep learning models.

But more importantly—and this is why I think OpenAI chose Microsoft over Amazon—is Microsoft’s reach across different industries. Thousands of organizations and millions of users are using Microsoft’s paid applications such as Office, Teams, Dynamics, and Power Apps. These applications provide perfect platforms to integrate GPT-3.

Microsoft’s market advantage is fully evident in its first application for GPT-3. It is a very simple use case targeted at a non-technical audience. It’s not supposed to do complicated programming logic. It just converts natural language queries into data formulas in Power Fx.

This trivial application is irrelevant to most seasoned developers, who will find it much easier to directly type their queries than describe them in prose. But Microsoft has plenty of customers in non-tech industries, and its Power Apps are built for users who don’t have any coding experience or are learning to code. For them, GPT-3 can make a huge difference and help lower the barrier to developing simple applications that solve business problems.

Microsoft has another factor working to its advantage. It has secured exclusive access to the code and architecture of GPT-3. While other companies can only interact with GPT-3 through the paid API, Microsoft can customize it and integrate it directly into its applications to make it efficient and scalable.

By making the GPT-3 API available to startups and developers, OpenAI created an environment to discover all sorts of applications with large language models. Meanwhile, Microsoft was sitting back, observing all the different experiments with growing interest.

The GPT-3 API basically served as a product research project for Microsoft. Whatever use case any company finds for GPT-3, Microsoft will be able to do it faster, cheaper, and with better accuracy thanks to its exclusive access to the language model. This gives Microsoft a unique advantage to dominate most markets that take shape around GPT-3. And this is why I think most companies that are building products on top of the GPT-3 API are doomed to fail.

The OpenAI Startup Fund

And now, Microsoft and OpenAI are taking their partnership to the next level. At the Build Conference, Altman declared a $100 million fund, the OpenAI Startup Fund, through which it will invest in early-stage AI companies.

“We plan to make big early bets on a relatively small number of companies, probably not more than 10,” Altman said in a prerecorded video played at the conference.

What kind of companies will the fund invest in? “We’re looking for startups in fields where AI can have the most profound positive impact, like healthcare, climate change, and education,” Altman said, to which he added, “We’re also excited about markets where AI can drive big leaps in productivity like personal assistance and semantic search.” The first part seems to be in line with OpenAI’s mission to use AI for the betterment of humanity. But the second part seems to be the type of profit-generating applications that Microsoft is exploring.

Also from the fund’s page: “The fund is managed by OpenAI, with investment from Microsoft and other OpenAI partners. In addition to capital, companies in the OpenAI Startup Fund will get early access to future OpenAI systems, support from our team, and credits on Azure.”

So, basically, it seems like OpenAI is becoming a marketing proxy for Microsoft’s Azure cloud and will help spot AI startups that might qualify for acquisition by Microsoft in the future. This will deepen OpenAI’s partnership with Microsoft and make sure the lab continues to get funding from the tech giant. But it will also take OpenAI a step closer toward becoming a commercial entity and eventually a subsidiary of Microsoft. How this will affect the research lab’s long-term goal of scientific research on artificial general intelligence remains an open question.

This article was originally published by Ben Dickson on TechTalks, a publication that examines trends in technology, how they affect the way we live and do business, and the problems they solve. But we also discuss the evil side of technology, the darker implications of new tech, and what we need to look out for. You can read the original article here.

Naabiae Nenu-B is a Medical Health Student and an SEO Specialist dedicated to flushing the web off fake news and scam scandals. He aims at being "Africa's Best Leak and Review Blogger" and that's the unwavering stand of Xycinews Media.

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The newest Nest Thermostat rarely goes on sale, but it’s $99.98 for Prime Day



If you purchase an independently reviewed product or service through a link on
our website, we may receive an affiliate commission.

The first-generation Nest Learning Thermostat crammed a wide range of brilliant convenience and energy-saving features into a design that was sleek and stylish. Needless to say, it was a total game-changer when it was first released. One simple device could not only save you a bunch of money and make controlling your HVAC system more convenient, but it also looked so cool and futuristic compared to all the regular thermostats out there. After all, they were just a bunch of ugly white boxes. Long story short, the Nest Learning Thermostat had it all.

So many people out there think that Nest’s flagship thermostat is still the best smart thermostat on the planet, and you won’t hear any arguments from us. In fact, we use the latest model in our own home and we love it. The problem is that the Nest Learning Thermostat is quite expensive compared to some of the newer options out there. Even while it’s on sale with a deep discount on Amazon, it’s still nearly $200. The good news is that you can get all the smart features that make Nest’s Learning Thermostat so great in the newer, less expensive model called simply the Nest Thermostat. It retails for $130 and that’s already a bargain, but pop over to Amazon right now and you’ll see that the Nest Thermostat is on sale with a rare discount for Prime Day that drops it to the lowest price ever!

The newest Nest Thermostat doesn’t have the same sleek stainless steel design as the flagship model. But if you ask us, it features a different design that’s just as stylish. The face of the new Nest has a unique mirror finish with a digital display underneath it, and it comes in four different colors to match any home decor. Most importantly, of course, the Nest Thermostat includes all of the important smart features from the flagship model. You’ll be able to control your thermostat from anywhere using the Nest app or your voice thanks to Google Assistant and Alexa support, and you’ll save plenty of money on your energy bill thanks to Nest’s intelligent features that tune your settings constantly and learn from your behavior.

With a list price of just $130, Google’s newest Nest Thermostat is a terrific value. All things considered, it may very well be the best value out there and it’s going to pay for itself in savings on your energy bills. But if you head over to Amazon right now and pick one up, you’ll pay just $99.98!

The only bad news is that we’ve seen this discount disappear already on a few different color options, so you probably don’t have much time left if you want to get in on the action. If you do miss out on this deal, the good news is that you can still snag the flagship Nest Learning Thermostat for just $199.

Google Nest Thermostat – Smart Thermostat for Home – Programmable Wifi Thermostat – Snow Price:$99.98 Available from Amazon, BGR may receive a commission Buy Now
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Here are some of the important details:

  • The Nest Thermostat is an ENERGY STAR-certified smart thermostat that combines efficiency with convenience
  • Works with or without a C wire in most homes
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  • Nest’s learning features let the thermostat automatically turn your AC or heat off when you leave, and back on when you arrive home
  • Controllable using the Nest app on iOS and Android devices, or with voice commands thanks to support for Alexa and Google Assistant
  • The special “Savings Finder” feature suggests tweaks to your schedule to help you save even more money while still remaining comfortable
  • Monitors your HVAC system and sends you an alert if something isn’t working properly

Google Nest Thermostat – Smart Thermostat for Home – Programmable Wifi Thermostat – Snow Price:$99.98 Available from Amazon, BGR may receive a commission Buy Now
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Follow @BGRDeals on Twitter to keep up with the latest and greatest deals we find around the web. Prices subject to change without notice and any coupons mentioned above may be available in limited supply.

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Keep your allergies at bay with this Prime Day deal on air purifiers



Chris Hachey handles e-commerce and sponsored content for BGR. He has worked as an editor and writer for over a decade for various publications and distribution services. He focuses on consumer products to help you find the best of what’s on the market. When he’s not searching for the top deals, he’s likely watching his favorite sports teams or walking around his hometown with his fiancée and his dog.

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Amazon’s Prime Day smart TV prices are so low, it seems like someone made a mistake



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If you’re a BGR Deals reader, you’ve undoubtedly been following along with our coverage all day and you’ve saved a ton of cash on all the most popular products out there. Highlights from our coverage so far include FREE MONEY from Amazon (send yourself a $40 eGift card, get a free $10 Amazon credit), deep discounts on pretty much every popular Apple device you can think of including AirPods Pro and the Apple Watch, a new all-time low price on the hot new TP-Link Kasa smart plugs that everyone loves so much, the best Instant Pot deals of the year with prices starting at just $49.99, AirPods 2 for just $99.99, the crazy wireless camera that lets your smartphone see anywhere for an all-time low price of $28.85, the Fire TV Stick Lite for a new all-time low price of $17.99 and the Fire TV Stick 4K for an all-time low of $24.99 instead of $50, the $80 Echo Show 5 for the all-time low price of $44.99, an Echo Show 5 and Blink Mini Cam bundle for just $10 more, the best-selling Echo Dot for only $19.99, the new 4th-generation Echo Dot for half price at $24.99, the $50 Echo Auto that adds hands-free Alexa to your car for an all-time low of $14.99 or the $98 Echo Auto bundle with 6 months of Amazon Music Unlimited for the same crazy price of $14.99, Echo Buds true wireless earbuds starting at just $79.99 instead of $120, and so much more.

All of those deals are fantastic indeed, but there’s also a slew of Fire TV deals that you need to check out right now. Incredibly, a whopping 18 different smart TV deals are available right now on the site!

The Fire TV lineup is neck and neck with Roku in terms of popularity among our readers (there are a bunch of excellent Roku deals available right now at Amazon by the way, including the hot new Roku Express 4K+ for just $29.99). Now, some of the best products in Amazon’s Fire TV portfolio are even more affordable thanks to deep discounts.

There is perhaps no streaming media player at the $50 price point that comes anywhere close to matching the Fire TV Stick 4K, which is on sale right now for $39.99. But if you’re in the market for a new smart TV, there are so many deals you need to see. Amazon is offering incredible discounts on 18 different Fire TV Edition televisions ranging in size from 24 inches all the way up to 70 inches. “Fire TV Edition” means Amazon’s Fire TV streaming software is built right into the TV, so you don’t need to worry about getting a separate media player.

Prices start at just $99.99 for an Insignia 24-inch Smart Fire TV, and the #1 best-seller of the bunch is the Toshiba 32-inch Smart Fire TV that’s on sale for $129.99 instead of $200. You can also pick up Insignia’s 43-inch Smart Fire TV for $219.99, down from $320, and Toshiba’s 50-inch Smart Fire TV that typically sells for $430 is on sale for $309.99.

Want to go bigger? Don’t worry because Amazon’s got you covered. The Insignia 65-inch Smart 4K Fire TV that normally sells for $630 is down to just $449.99 right now, and the massive Insignia 70-inch Smart 4K Fire TV that retails for $700 is on sale for just $529.99 if you’re a Prime member. That price is so low, it seems like someone made a mistake!

You can see all 18 deals on this special Amazon page, and you’ll find a few of our favorites down below.

Fire TV Sticks

  • The Fire TV Stick 4K is Amazon’s most powerful streaming media player ever with the popular dongle form factor
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  • Plenty of games and other apps to choose from in Amazon’s app store
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Fire TV Edition Televisions

INSIGNIA NS-70DF710NA21 70-inch Smart 4K UHD – FireTV, Released 2020 List Price:$699.99 Price:$529.99 You Save:$170.00 (24%) Available from Amazon, BGR may receive a commission Buy Now
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All-New Insignia 55 inch NS-55F301NA22 F30 Series LED 4K UHD Smart Fire TV, Released 2021 List Price:$499.99 Price:$349.99 You Save:$150.00 (30%) Available from Amazon, BGR may receive a commission Buy Now
INSIGNIA NS-65DF710NA21 65-inch Smart 4K UHD – Fire TV, Released 2020 List Price:$629.99 Price:$449.99 You Save:$180.00 (29%) Available from Amazon, BGR may receive a commission Buy Now

Follow @BGRDeals on Twitter to keep up with the latest and greatest deals we find around the web. Prices subject to change without notice and any coupons mentioned above may be available in limited supply.

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