Bloomberg initially reported last week that Microsoft is in talks with Open AI, the firm that developed the well-known A.I. chatbot called ChatGPT that recently caught the internet by storm, to invest as much as $10 billion in the company. In a note to clients on Wednesday, Wedbush tech analyst Dan Ives referred to ChatGPT as one of the "most inventive A.I. technologies" in history and "a possible game changer" for Microsoft.

He said that amid the global AI weapons race, Microsoft is turning into a "central A.I. play" for investors, writing, "We feel this strategic investment is a smart poker move."

The price of Microsoft shares has increased by around 3% recently but has decreased by almost 25% over the previous year because of the general bear market. Ives, though, asserted that OpenAI's technology will find wide use at the multinational tech company and that, over the following ten years, it will be "completely integrated" into the company's whole product line.

Microsoft has previously dabbled in the artificial intelligence space, so this isn’t their first exposure to the nascent technology. To create new A.I.-enabled supercomputing technologies for its cloud platform, Azure, the tech giant, even invested $1 billion in OpenAI back in 2019. The company has been developing its own A.I. technology for years (check out VALL-E, the A.I. that can copy your voice after listening to a three-second audio clip). Microsoft is apparently taking another bite at the AI apple now that OpenAI has raised money at a $29 billion valuation and attracted over 1 million users to ChatGPT less than a week after its launch in early December. Ives thinks this is the appropriate strategy.

He said, referring to Microsoft CEO Satya Nadella, "While ChatGPT is inherently a high cash burn situation today, we view this as a strategic step for Nadella & Co. to double down on its artificial intelligence strategy as new use cases raise unprecedented demand for AI solutions."

Ives asserted that by integrating ChatGPT into the Office suite of programs and employing the technology to give users better search results with Bing, Microsoft will be able to challenge Google's hegemony over the industry. According to Statcounter, Bing only accounts for 3% of the global search engine industry at the moment, while Google holds 93% of the market. Ives, however, thinks that might change if Microsoft can provide "more sophisticated search capabilities and language models."

Ives additionally asserted that Microsoft's video game division might use OpenAI's technology. Activision Blizzard, one of the biggest gaming firms in the world, is presently being purchased by Microsoft for $69 billion. However, it has run into opposition from the U.S. Federal Trade Commission (FTC) and the U.K. Competition and Markets Authority (CMA), both of which contend that the acquisition will stifle competition in the gaming sector.

Ives said that Microsoft will ultimately prevail in its "fight" with the FTC, saying that this is "another move for the corporation to double down on its gaming endeavors with this technology finding further applications inside the video game and digital art business."

However, not everyone is as optimistic about the potential game-changing application of AI. Teachers have started to question whether ChatGPT spells the end of the college essay after some critics have dubbed it unsafe. Elon Musk, CEO of Tesla, previously referred to AI in general as "summoning the demon" in a 2014 interview. Elon Musk was also one of OpenAI's early backers.
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Musk stated in a tweet on December 3 that ChatGPT was "scary good" and that "we are not far from dangerously strong A.I." However, Ives thinks that for investors, developments in artificial intelligence might be a gold mine, with Microsoft being one winner. He has a buy rating of "Outperform" and a $290 12-month price objective for the company. The company recently closed at $239.

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.