ChatGPT was created by the technology company OpenAI. Microsoft is now testing the AI language as an enhancement to its Office suite of products, including Word, Outlook and PowerPoint.

OpenAI has had a lot of press lately given that their AI products ChatGPT and Dall-E 2

For their ability to produce text and images, OpenAI's intuitive technology products, such as ChatGPT and Dall-E 2, have become online sensations. Many people have made assumptions about the ethical and practical use of ChatGPT. Microsoft is attempting to make better use of the company's AI models, though. According to The Information, the business has already updated its autocomplete feature with a version of the OpenAI GPT text-generator model.

Microsoft has been testing GPT AI model functionality in Outlook and PowerPoint. These include tools that enable users to locate Outlook search results in email inboxes using speech-like AI-driven commands rather than keywords. Additionally, AI models for Outlook and Word will propose email responses or offer edits to documents to improve writing abilities. There is no information yet on whether this use will eventually be incorporated into consumer-facing versions of Microsoft Office or if the company is merely exploring the GPT model's potential.
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Microsoft invested $1 billion in OpenAI in 2019, and according to the report, "acquired an exclusive license to the underlying technology behind GPT-3 in 2020," before this practical application of the GPT technology.
Microsoft may aim to integrate the GPT AI model into its Bing search engine besides its Office suite to compete with Google. According to The Verge, this could be the item that is most likely to be released, with a potential release date of March.

Making data-driven decisions is becoming more and more understood by companies in every industry as a requirement for competing today, in the next five years, in the next twenty, and beyond. According to current market research, the worldwide artificial intelligence (AI) market will "increase at a compound annual growth rate (CAGR) of 39.4% to reach $422.37 billion by 2028," driven by the exponential expansion of unstructured data in particular. The era of data overload and AI has arrived, and there is no turning back.
This reality implies that AI can truly sift and handle the deluge of data–not just for big giants like Alphabet, Microsoft, and Meta with their massive R&D departments and tailored AI tools, but for the typical corporation and even some small and medium-sized businesses.

Well-designed AI-based systems quickly filter through enormously vast datasets to produce fresh insights, which fuel fresh sources of income, adding significant value to enterprises. But without the new kid on the block, vector databases, none of the data expansion really becomes operationalized and democratized. Vector DBs represent a paradigm shift in database management and a new category for using the exponential amounts of unstructured data that are currently untapped in object stores. In particular, vector databases provide a mind-numbing new degree of search capacity for unstructured data, but they can also handle semi-structured and even structured data.

Vectors and Search. Unstructured data, which can't be simply sorted into row and column relationships, rarely matches the relational database paradigm. Examples include photos, video, audio, and user actions. Unstructured data management methods that are incredibly time-consuming and unreliable frequently include manually labelling the data (think labels and keywords on video platforms).

The real problem is that human methods make it very hard to perform a semantic search that comprehends the context and meaning of a picture or other unstructured piece of data, in addition to a search query.
Enter embedding vectors, often known as feature vectors, vector embeddings, or just embeddings. They are numerical values, or sort of coordinates, that represent unstructured data features or objects, such as a part of a picture, a section of a person's purchasing history, a few frames from a video, geospatial information, or anything else that doesn't neatly fit into a relational database table. These embeddings enable scalable, snappy “similarity search.”

Quality Data and Insights. An AI model, or more precisely, a machine learning (ML) or deep learning model, trained on very large amounts of high-quality input data, produces embeddings as a computational byproduct. A model is the computational result of an ML algorithm (method or procedure) conducted on data, to further draw crucial distinctions. Sophisticated, widely used algorithms include STEGO for computer vision, CNN for image processing and Google’s BERT for natural language processing. The resulting models turn each single piece of unstructured data into a list of floating-point values—our search-enabling embedding.

Therefore, a neural network model that has been properly trained will produce embeddings that are consistent with particular content and may apply to a semantic similarity search. A vector database, specifically designed to manage embeddings and their unique structure, is the instrument to store, index, and search through these embeddings.

The fact that developers from everywhere may now incorporate a vector database into AI systems, with its production-ready features and lightning-fast unstructured data search, is crucial in the industry.
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Organizationally, a crucial component of standardizing the usage of vector databases is assisting business teams and their leadership in understanding why and how they can benefit. The concept of vector search has been around for quite a while, but only on a very small scale. Many businesses aren't really accustomed to having access to the kind of data mining and search capabilities that contemporary vector databases provide. Teams sometimes struggle with knowing where to begin. Therefore, their creators continue to place a high focus on spreading the word about how they operate and why they are valuable.

Laptops have come of age in the last few years. Their processing power and memory have increased to where they can rival most desktop computers. The only problem is that they are made to be thin and portable and there are few ports to support peripherals. There are a lot of connection docks out on the market for both windows-based and Apple laptops. Today I want to share one that, while it's pricier than many, is not only a quality product but delivers on making your laptop into a desktop unit.

Sandberg now has a USB-C All-in-1 docking station that I think stands apart from its competition. First is its design. It is made to fit under the back of your laptop, providing an ergonomic tilt to the keyboard and conserving the limited space you have (think airline fold-down tables.) It also helps if your laptop is running hot by allowing better airflow.
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Here are the specifications:

• Aluminum construction, 11.6 ounces, 10.6” X 2.9” X .8”
• 1 x USB-C (power supporting up to 100W), 1 x HDMI, 1 Mini DisplayPort, 1 x VGA female, 3 x USB 3.0 A, 1 x RJ45, 1 x audio output, 1 x security lock slot
• 1 x SD card reader slot supporting SD/SDHC/SDXC/MMC
• Micro SD/TF card reader slot
• RJ45 connector supporting 10/100/1000 Mbps Ethernet
• 3.5mm audio jack supporting audio sample rate at 192KHz/24bit
• HDMI Resolution up to max 4K/2K @ 30Hz (1920 x 1080P @ 60Hz)
• DisplayPort resolution up to 4K/2K @ 30Hz (1920 x 1080P @ 60Hz)
• VGA resolution up to 1920 x 1080P @ 60Hz
• Supports simultaneous output at DisplayPort+HDMI and DisplayPort+VGA
• Automatic recognition of monitor type, resolution, and features

Farming takes place in fields, greenhouses, and orchards, but photovoltaic (PV) cells require their own land to harness the sun's energy and generate electricity. The two weren't thought to live together well.

Two professors  from the Hebrew University of Jerusalem,  Prof. Lioz Etgar of the Institute of Chemistry and Prof. Haim Rabinowitch of the Smith Faculty of Agriculture, Food, and Environment, have now worked together to create a prototype for a revolutionary PV cell. The new cell's performance has the potential to alter the laws of the solar energy and agricultural production game because its efficiency has been technologically shown.

The innovative solar cell is made to cover completely agricultural areas, such as greenhouses, orchards, fields, and water bodies, while generating green electricity and agricultural production simultaneously, without interfering with the natural habitats beneath the PV panels, without depleting natural resources, and without endangering the environment.

The team estimates this breakthrough will lower Israel's energy costs by 75%. In fact, they think that if Israel covered half of its greenhouses with these new cells, green electricity output would exceed Israel's national target for that year.

The new solar cells are built on crystals of perovskite, a mineral that was first found in 1839 and is a calcium titanium oxide that is reasonably simple to produce using inexpensive and readily available materials.

A chemical substitution makes the solar cells transparent to the most efficient area of the light spectrum that drives photosynthesis. A great part of the rest of the light energy is transformed into electricity.

“For years, it has been obvious that most light energy in agricultural greenhouses is wasted, as plants use only a fraction of the sunlight energy, while the rest is radiated back into the atmosphere,” Etgar explained. “In greenhouses, it becomes heat energy that growers need to get rid of during most months of the year. Our solution maximizes the production of solar electricity on agricultural land by up to 300%.”

Compared to silicon-based photovoltaic cells, the new cells are expected to have significantly reduced production costs. They will probably also significantly improve cultivation conditions in greenhouses by reducing heat, lowering greenhouse gas emissions and evapotranspiration, saving water, and protecting crops from weather damage.

All currently used methods for producing green energy on agricultural lands use silicon-based photovoltaic cells that are entirely or somewhat opaque to most visible light spectrums or are arranged in different arrays. Because of this, power generation is less efficient and agricultural production is consequently decreased.

Rabinowitch added, “This new development, which can be installed over any agricultural lands and any bodies of water, will make it possible to fully replace the roofs of most agricultural greenhouses, reduce heat levels and evapotranspiration in orchards and fields, and impairment of many fresh-water and coastal marine ecosystems on which rafts, or islands of solar cells are installed.”

Using these new cells will reduce agricultural costs and raise agricultural income and profitability, according to calculations based on existing data. The researchers declared that this was nothing short of a revolution.
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Israel has around 90,000 dunams [approximately 35 square miles] of greenhouses. Covering half of the greenhouse roofs with the new solar cells will provide a quantity of green electricity that enables Israel to exceed its 2050 national targets for green electricity production and carbon emission reduction. To put this development into perspective, the Mediterranean basin alone holds around two million dunams (770 sq. mi.) of greenhouses.

Employees and managers alike continue to debate the pros and cons of working remotely. Many workers desire to keep their flexible schedules, lower costs, and improved work-life balance. On the other side, some managers and executives believe that for employees to be fully engaged in their work, they must be present in the workplace.

A Harvard Business Review (HBR) article claims that reducing employees' sense of alienation from their coworkers and the corporate culture is a compelling justification for getting them back to the office. Studies have shown that remote workers are more inclined to leave their jobs when they feel alienated and separated.

These emotions of loneliness can be lessened by encouraging employees to socialize and assigning them a talking companion. For remote and hybrid workers who live in the same city, employers can arrange gatherings to lessen their sense of loneliness.

Many firms argue that returning to the workplace is necessary to boost worker productivity, since people are less productive at home than they are at work.

But the HBR analysis shows just the opposite. Following the COVID-19 lockdowns in April through mid-May 2020, researchers collected metadata from all Zoom, Microsoft Teams, and WebEx meetings (with webcams on or off) from ten sizable international organizations. They then compared this set of six weeks in 2021 and 2022 with the same set of six weeks in 2020.

The study concluded that, while remote work doesn't reduce productivity; it does alter how both employees and employers define productivity. The habits of remote employees changed in 2022 as compared to 2020, when it was novel.

The survey found virtual meetings are more common today. They’re more spontaneous, condensed, and with fewer people. We can assume that as remote working became more ubiquitous, people realized that sometimes it's unnecessary to have a 30-minute to an hour-long meeting.

The HBR study found that meetings were 10 minutes shorter in 2022 than they were in 2020, and 66% of one-on-one meetings were unscheduled. In contrast to the strict timetables organizations followed prior to the epidemic, these statistics can be attributed to managers and employees arranging meetings on an as-needed basis.

Another interesting fact from the research found that meeting attendance decreased by 50%, from an average of 20 participants to 10. According to HBR, this decline was brought on by a rise in one-on-one meetings in 2022, when 42% of meetings were one-on-ones, up from 17% in 2020.

The goal of the HBR study was to refute the claim that remote workers are not interacting with their coworkers. Unplanned one-on-one meetings, according to the report, may take the place of the face-to-face interactions that employees once had at work.
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Although the ways that we work now are different and might change more over time, it's clear that people are still working. Bottom line: Does it really matter where employees are working as long as they finish their tasks on time and meet their targets?

Regardless of the business you work for, networking is a key skill for success. But in the contemporary environment we live in, creating and distributing business cards doesn't really make sense.

An alternative that is more environmentally friendly is a new electronic card called the Linq card that digitally sends your contact information to someone else's phone. 

The Linq business card looks exactly like a standard business card, but it has a significant difference: it can instantly share your contact information with others by tapping it on a smartphone.

The card makes use of a near-field communication (NFC) chip, the same technology that powers regular activities like using your smartphone to make in-store purchases, to enable the tap-sharing feature. Most devices have NFC reading capabilities, but if the person you want to share with doesn't have NFC, you can still easily share your information by having them scan the QR code on the back of the card.

The Linq profile is displayed once the person taps the card or scans the QR code. When you first activate your card, the Linq app prompts you to create your unique profile. The best feature is how customizable it is—from the design of your bio page to the social media platforms and links that are displayed, right down to the reference profile picture and even an included video.

If you meet regularly with new businesses and individuals, they offer an option for you to save the contact information on those with whom you share your information. The recipient has the option to add your contact information automatically to their default messaging app when it is scanned.

The traditional white card is the least expensive option in terms of price, coming in at $12 on Linq’s website; prices rise as you choose different color options, finishes and additional custom features.
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Regardless of age, these cards make wonderful stocking stuffers or presents for everyone who works.

New chips are being released by Amazon.com Inc.'s cloud computing division to power the most advanced computing, supporting tasks like gene sequencing and weather forecasting.

The largest provider of cloud computing, Amazon Web Services (AWS), announced recently that it will allow users to rent processing capacity that uses a new generation of its Graviton chips. The product, according to Peter DeSantis, senior vice president and manager of most of AWS' technical teams, is a platform for expanding access to high-performance computing.

The newest chip is Amazon's most recent push to produce more of the hardware for its large data centers that power AWS. Making its own chips, according to Amazon, will provide clients access to more powerful computers at a lower cost than they could by renting time on processors made by companies like Intel Corp., Nvidia Corp., or Advanced Micro Devices Inc. These businesses, which are also some of AWS's biggest suppliers, are now in direct competition with it because of the new chips. According to DeSantis, the chipmakers are still "excellent partners," and AWS intends to keep providing high-performance computing services based on their chips.

To kick-start its in-house chip designs, which initially were concentrated on basic computing activities like serving as the foundation for websites, AWS bought chipmaker Annapurna Labs in 2015. The high-performance computing initiative, which was unveiled at the opening of the AWS re:Invent trade conference, aims to show that Amazon's proprietary technology can compete head-to-head with chips from leading manufacturers.

The Inferentia chip, which is made to make deductions from enormous volumes of data, has undergone an update, according to AWS Chief Executive Officer Adam Selipsky, who made the announcement the second day of the re:Invent conference. According to Amazon, Inferentia2 handles larger data sets than its predecessor, making it possible to perform tasks like software-generated graphics or speech recognition and interpretation.

Among the most sophisticated systems powered by cutting-edge semiconductors are computers that forecast weather patterns and simulate the aerodynamics of race cars. Usually, enterprises, government agencies, and academic institutions have created pricey computer systems in their own data centers using components from Intel, Nvidia, and AMD.

According to DeSantis, the Graviton3E, the most recent model in AWS's line of Graviton processors, will be twice as capable as earlier models in one category of calculations used by high-performance computers. When combined with other AWS technology, the new offering will be 20% better than the previous one. Amazon didn't say when services based on the new chip would be available.
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“The reason that high-performance computing isn’t big is it’s hard,” DeSantis said. “It’s hard to get capacity, it’s hard to get time on that supercomputer. What we’re excited about is bringing the capabilities of high-performance computing to more workloads.”

To keep up with the ever-growing numbers in our digital world, we need more unit measurements for larger numbers as more digital data is produced and stored and smaller numbers for quantum science and particle physics.

The last time this was done was 1991 when we added two larger prefixes – zetta [Z] (1 with 21 zeroes) and yotta [Y] (1 with 24 zeroes) and two smaller prefixes – zepto [z] (21 zeroes to the right of the decimal point) and yocto [y] (24 zeroes).

Now, the 27th General Conference on Weights and Measures introduced four new prefixes to the International System of Units, or metric system. On the “larger” scale, the first new prefix is ronto [R] (1 with 27 zeroes) and quecto [Q] (1 with 30 zeroes). On the “smaller” scale, the two new prefixes are ronna [r] (27 zeroes to the right of the decimal point) and quetta [q] (27 zeroes.)

"Most people are familiar with prefixes like milli- as in milligram," Richard Brown, head of metrology at the U.K.'s National Physical Laboratory who proposed the four new prefixes, told The Associated Press. "But these [new additions] are prefixes for the biggest and smallest levels ever measured."

On the larger scale, we can now state the Earth’s mass as 6 ronnagrams rather than 6,000 yottagrams. The sun is 2,000 quettagrams rather than 2,000,000,000 yottagrams. On the smaller scale, now an electron’s mass is said to be 1 rontogram rather than 0.001 yoctograms.
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"It was high time. [We] need new words as things expand," Brown said. "In just a few decades, the world has become a very different place."

There is a device from a small company named Edge that could be that standout stocking stuffer for that special someone who works from home or a deserving college student. The EDGE® Kit attaches to the back of any device with a suction cup. A variety of devices can then be attached to the swing-out arm: a light for online conferencing, a smartphone to add a second screen to the work mix or a wireless Qi charger for the side of your desktop’s monitor.

Attach a Phone. Most users will attach the EDGE® Kit to their display monitor. It's attached with a suction cup on one side of its bending arm. Watch that podcast or a movie from the side of your monitor, or put the Kit on top of the screen and use your phone as a camera for video conferencing.

Wireless Charging. The EDGE® Kit includes a wireless Qi charging coil that’s compatible with iPhone MagSafe devices (iPhone 8 and above) or any Android device that supports wireless charging. You can also kill two birds at once by putting the phone on the charger and then watching that movie or podcast!

In what's being hailed as an important first for chemistry, an international team of scientists has developed a new technology that can selectively rearrange atomic bonds within a single molecule. The breakthrough allows for an unprecedented level of control over chemical bonds within these structures and could open up some exciting possibilities in what's known as molecular machinery.

Molecules comprise clusters of atoms and are the product of the nature and arrangement of those atoms within. Where oxygen molecules we breathe feature the same repeating type of atom, sugar molecules are made of carbon, oxygen and hydrogen.

To create precisely the chemical interactions between atoms they desire, scientists have been working on a concept known as "selective chemistry" for some time. This could cause the development of sophisticated chemicals and machinery that can be tailored for specific purposes.

The 2016 Nobel Prize in Chemistry was awarded to Dutch scientist Ben Feringa for his development of a molecular car propelled by molecular motors spinning at 12 million revolutions per second. These so-called molecular machines were the subject of the award. To specifically target cancer cells, scientists have also developed molecular pumps, small gear wheels, and molecular submarines, to name a few examples.

This new study's authors compare “putting Lego bricks in a washing machine and hope that the quintillions of molecules somehow manage to assemble themselves into the intended product.” Their latest research hopes to rely more on deliberate control of the chemical bonding process and less on chance.

The study focuses on molecules known as structural isomers, which share the same atomic structure but differ in the way those atoms are connected to one another. The researchers showed they could specifically rearrange the chemical interactions by applying different voltage pulses using the tip of a scanning probe microscope. It was possible to change a molecule with a 10-membered carbon ring in the middle into, for instance, a molecule with a 4- and 8-member ring or a molecule with two 6-member rings in the middle.

The scientists discovered these processes were also reversible, allowing them to flip between different molecular configurations in a controlled way by arbitrarily breaking and forming the various connections. The team claims that this type of "selective chemistry" is unique.

Leo Gross, an IBM Research scientist and the senior author of the study, said “it is the first time that selectivity different bonds can be formed in a single molecule. By the magnitude of the voltage pulse applied on the molecule in the center, we can choose if we want to create the molecule on the right or the one on the left (see above left).”

Although molecular machinery is still in its infancy, technology that allows for more precise control over these kinds of structures may drastically speed up their development.

The movement of molecules or nanoparticles, the creation and manipulation of nanostructures, and the facilitation of chemical reactions are just a few of the activities that molecular machines may be used, according to Gross. Future uses could involve medication delivery, chemical synthesis, nanoelectromechanical systems, and single-electron molecular devices.