Trending February 2024 # Top 7 Smartphones To Be Released In February 2023 # Suggested March 2024 # Top 2 Popular

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From the speculations so far, five or six smartphones with the new Snapdragon 8 Gen1 will launch in February. We have the likes of the Redmi K50 series, Samsung Galaxy S22 series, etc. Of course, several brands will use the new flagship processor for their gaming smartphones. Redmi K50 e-sport version, Nubia Red Magic 7 series, Lenovo Legion Y90 gaming phone will all use this chip

Now, let us take a look at the top 7 smartphones that we expect to launch next month

1. Samsung Galaxy S22 series

As a major mobile phone manufacturer, Samsung Galaxy S22 series have been exposed for many months. It’s a norm for the full specs of the Galaxy S series to hit the web before its launch. This time is not any different.

The screen sizes of the three (Galaxy S22, S22+, and S22 Ultra) models are 6.06, 6.55, and 6.81 inches respectively, and the highest is equipped with a QHD+ high-definition screen. The Ultra version will be equipped with a 1/1.33-inch 108-megapixel HM3 improved main camera, f1.8, FOV 85. There is also a 12-megapixel wide-angle lens + two 1-megapixel telephoto lenses. This smartphone will also come with a built-in 5000 mAh battery that supports 15W fast charge.

2. Redmi K50 series

The Redmi K50 series is a very diverse series that will have four models all with different processors. This series will have the Redmi K50, K50 Pro, K50 Pro+ and K50 gaming edition. These models will use the Snapdragon 870, Dimensity 8000, Dimensity 9000, and Snapdragon 8 Gen1 chips respectively.

Just like the flagship Xiaomi 12 series, the Redmi K50 series will also support 120W fast charging. However, not all models will have this feature. Nevertheless, the Redmi K series is mainly cost-effective and its starting price will be around 1999 yuan ($315).

From the information so far, the Redmi K50 gaming edition will arrive first. In addition to the Snapdragon 8 Gen1 SoC, this smartphone will also use a 6.67-inch center punch-hole screen.

The dimension is 162 x 76.8 x 8.5 mm and it weighs 210g. In terms of appearance, it will be the same as the Redmi K40 gaming edition. However, this smartphone will come with a built-in 4700 mAh battery that supports a 120W fast charge. This device will also have the JBL dual speakers, a new generation AAC 1016 ultra-wideband X-axis motor, as well as shoulder keys. It will be the most expensive model in the series and its price should exceed 3000 yuan ($473).

All the smartphones in this series will use a side fingerprint sensor as well as up to 12GB of RAM. The Redmi K50 score on GeekBench is 963 (single-core score) and 3123 (multi-core score).

3. Realme GT Neo3

From the speculations so far, the Redmi GT Neo3 with Dimensity 8000 SoC will be official next month. This smartphone comes with a 6.5-inch FHD+ screen that supports a 120Hz refresh rate. In the camera department, this smartphone comes with a 64MP main camera as well as two 2MP cameras to make up its triple rear camera setup. The price may be less than 2,000 yuan ($316), which is very cost-effective.

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The previous Realme GT Neo was the first to launch the Dimensity 1200 mobile platform. The Realme GT Neo2T is also the world’s first Dimensity 1200 AI smartphone. According to the usual practice, there is a high possibility that the GT Neo3 will be the first smartphone to use the Dimensity 8000.

4. Vivo NEX5 & Vivo Pad – the return of technological innovation

Vivo NEX5 has been officially confirmed and this smartphone will be official in February. In addition to the confirmed Snapdragon 8 Gen1 SoC, this smartphone adopts a 2K E5 screen with a punch-hole of about 7 inches. Furthermore, this flagship smartphone will come with a built-in 5000 mAh dual-cell battery that supports an 80W fast charge.

At the same time, there is also a tablet product, Vivo Pad, which has a built-in 7860 mAh battery that supports a 44W fast charge. This tablet will probably debut in the same event as the Vivo NEX5. This tablet comes with the Snapdragon 870 which has a good reputation.

5. ZTE Z40 series & Nubia Red Magic 7 series – a new generation of Snapdragon 8 Gen1 phones

On January 20, ZTE officially announced that it will release two flagships on the same day. These smartphones are the Nubia Red Magic 7 series and ZTE Z40 series. Both smartphones will use the new Snapdragon 8 Gen1 processor. The Red Magic 7 will come with a 6.8-inch 2400 x 1080 resolution OLED screen, a front 8-megapixel lens, a rear 64-megapixel triple camera, and support 165W fast charging.

The Nubia Z40 series focuses on super image strength. It claims to be “the first customized optics in the mobile phone industry”. It adopts the industry’s only 35mm main camera, and the world’s first joint customized Sony IMX787. In addition, it supports SLR-level optical blur, f/1.6 large aperture, OIS, full-pixel focusing, etc., and the heat dissipation effect is equally strong.

6. Lenovo Legion Y90 dual-engine air-cooled gaming phone

This gaming smartphone will be official next month. It has a mid-frame structure design and will use a 6.92-inch FHD+ 144Hz symmetrical non-punch hole E4 OLED full screen. This smartphone also comes with a rear center lens as well as a built-in cooling fan. Just like other gaming smartphones, the Lenovo Legion Y90 will use the Snapdragon 8 Gen1 SoC.

According to official reports, “Honor of Kings” has an average frame rate of 119.8 frames in 30 minutes.

7. iPhone SE3

The iPhone SE3 is the most recently exposed smartphone from Apple. Although many expect this smartphone to arrive in February, there is no certainty that this is a February device.

This is Apple’s usual “cheap” smartphone which comes with a small screen. The iPhone SE3 is equipped with a single camera on the back, a 4.7-inch screen on the front, an A15 bionic chip, and a 5G connection.

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Top 10 Affordable Ai Stocks To Buy In February 2023

If you want to be rich in no time, you must invest in these top AI stocks in February 2023

Currently, the rise of artificial intelligence (AI),

NVIDIA Corp

Stock Price Today: US$243.19 Market Cap: US$606.029B Nvidia’s data center business represents a steadily increasing share of the company’s total revenue. This segment isn’t all AI-related — Nvidia’s graphics cards are used to accelerate a wide variety of data center applications. But

International Business Machines Corp.

Stock Price Today: US$137.15 Market Cap: US$122.93B IBM’s strategy with AI is to apply the technology in ways that augment human intelligence, increase efficiency, or lower costs. In the healthcare industry, IBM’s AI technology is being used to create individualized care plans, accelerate the process of bringing new drugs to market, and improve the quality of care. In the financial services industry, via the company’s 2024 acquisition of Promontory Financial Group, IBM is using Artificial Intelligence to help clients with the daunting task of financial regulatory compliance.  

Alphabet Inc

Stock Price Today: US$2,860.32 Market Cap: US$1.893T Google and YouTube parent company Alphabet uses AI stocks and automation in virtually every facet of its business, from ad pricing to content promotion to email spam filters. Alphabet has AI and

Micron Technology, Inc

Stock Price Today: US$81.17 Market Cap: US$90.893B Micron Technology manufactures memory chips, including dynamic random-access memory (DRAM) and NAND flash memory found in solid-state storage drives. Most of what the company makes are commodity products, meaning that supply and demand dictate pricing. In the future, demand for memory chips will only grow, and that’s especially true in the Artificial Intelligence industry. Self-driving cars are a good example. All the sensors and cameras produce a lot of data around 1 GB per second, according to Micron estimates. Data centers running AI stocks processes need plenty of memory and so do smartphones that may be doing AI work.  

Microsoft Corp.

Stock Price Today: US$305.94 Market Cap: US$2.294T In 2023, Microsoft announced the construction of a new supercomputer hosted in Azure, Microsoft’s cloud computing network. The supercomputer was built in collaboration with OpenAI LP to train AI models with the ultimate goal of producing large AI models and related infrastructure for other organizations and developers. In late 2023, Microsoft also debuted Context IQ, an Artificial Intelligence application that can predict, seek and suggest information for employees.   Stock Price Today: US$305.94 Market Cap: US$2.294T Amazon uses artificial intelligence for everything from Alexa, its industry-leading voice-activated technology, to its cashier-less grocery stores, to Amazon Web Services Sagemaker, the cloud infrastructure tool that deploys high-quality

Meta Platforms Inc.

Stock Price Today: US$237.09 Market Cap: US$645.345B  

C3.ai Inc

Stock Price Today: US$25.18 Market Cap: US$2.645B C3.ai is a SaaS company whose software allows companies to deploy large AI stocks applications. The company’s tools help its customers accelerate software development and reduce cost and risk, and they have a wide variety of applications. For example, the U.S. Air Force uses C3 AI Readiness to predict aircraft systems failures, identify spare parts, and find new ways to increase mission capability. European utility company Engie (OTC: ENGIY) is using C3 AI to analyze energy consumption and reduce energy expenditures.  

NICE Ltd.

Stock Price Today: US$254.50 Market Cap: US$16.123B NICE is a leading provider of software applications that manage call center operations and customer interactions. NICE’s AI and

DocuSign Inc.

Stock Price Today: US$118.46 Market Cap: US$23.441B

Top 7 Python Web Scraping Libraries & Tools In 2023

When it comes to web scraping, there are four common approaches for gathering data: 

Developers use web scraping libraries to create in-house web crawlers. In-house web crawlers can be highly customized, requiring  significant development and maintenance time. Building a web scraper in a language you are familiar with will allow you to reduce the development time and resources needed  to build the scraper.

Python is the most commonly used programming language of 2023.

In this article, we summarized the main features, pros and cons of the most common open-source Python web scraping libraries.

1. Beautiful Soup

Beautiful Soup is a Python web scraping library that extracts data from HTML and XML files.

Beautiful Soup Installation: You can install Beautiful Soup 4 with “the pip install beautifulsoup4″ script.

Prerequisites:

Python

Pip: It is a Python-based package management system.

Supported features of Beautiful Soup:

Beautiful Soup works with the built-in HTML parser in Python and other third-party Python parsers, such as HTML5lib and lxml.

Beautiful Soup uses a sub-library like Unicode and Dammit to detect the encoding of a document automatically.

BeautifulSoup provides a Pythonic interface and idioms for searching, navigating and modifying a parse tree.

Beautiful Soup converts incoming HTML and XML entities to Unicode characters automatically.

Benefits of Beautiful Soup:

Provides Python parsers like”lxml” package for processing xml data and specific data parsers for HTML.

Parses documents as HTML. You need to install lxml in order to parse a document as XML.

Reduces time spent on data extraction and parsing the web scraping output.

Lxml parser is built on the C libraries libxml2 and libxslt, allowing  fast and efficient XML and HTML parsing and processing.

The Lxml parser is capable of handling large and complex HTML documents. It is a good option if you intend to scrape large amounts of web data.

Can deal with broken HTML code.

Challenges of Beautiful Soup:

BeautifulSoup html.parser and html5lib are not suitable for time-critical tasks. If response time is crucial, lxml can accelerate the parsing process.

Most websites employ detection techniques like browser fingerprinting and bot protection technology, such as Amazon’s, to prevent users from grabbing a web page’s HTML. For instance, when you send a get request to the target server, the target website may detect that you are using a Python script and block your IP address in order to control malicious bot traffic.

Bright Data provides a residential proxy network with 72+ million IPs from 195 countries, allowing developers to circumvent restrictions and IP blocks.

2. Requests

Requests is an HTTP library that allows users to make  HTTP calls to collect data from web sources.

Requests Installation: Requests’s source code is available on GitHub for integration into your Python package. Requests officially supports Python 3.7+.

Prerequisites:

Python

Pip: You can import Requests library with the “pip install requests” command in your Python package.

Features of Requests:

Requests automatically decode web content from the target server. There’s also a built-in JSON decoder if you’re working with JSON data.

It uses a request-response protocol to communicate between clients and servers in a network.

Requests provides in-built Python request modules, including GET, DELETE, PUT, PATCH and HEAD, for making HTTP requests to the target web server.

GET: Is used to extract data from the target web server.

POST: Sends data to a server to create a resource.

PUT: Deletes the specified resource.

PATCH: Enables partial modifications to a specified resource.

HEAD: Used to request data from a particular resource, similar to GET, but does not return a list of users.

Benefits of Requests:

Requests supports SOCKS and HTTP(S) proxy protocols.

Figure 2: Showing how to import proxies into the user’s coding environment

Source: Requests

It supports Transport Layer Security (TLS) and Secure Sockets Layer (SSL) verification. TLS and SSL are cryptographic protocols that establish an encrypted connection between two computers on a network.

Challenges of Requests:

It is not intended for data parsing.

It does not render JavaScript web pages.

3. Scrapy

Scrapy is an open-source web scraping and web crawling framework written in Python.

Scrapy installation: You can install Scrapy from PyPI by using the “pip install Scrapy” command. They have a step-by-step guideline for installation for  more information.

Features of Scrapy:

Extract data from HTML and XML sources using XPath and CSS selectors.

Offer a built-in telnet console for monitoring and debugging your crawler. It is important to note that using the telnet console over public networks is not secure because it does not provide transport-layer security.

Include built-in extensions and middlewares for handling:

Robots.txt

User-agent spoofing

Cookies and sessions

Support for HTTP proxies.

Save extracted data in CSV, JSON, or XML file formats.

Benefits of Scrapy:

Scrapy shell is an in-built debugging tool. It allows users to debug scraping code without running  the spider to figure out what needs to be fixed.

Support robust encoding and auto-detection to handle foreign, non-standard, and broken encoding declarations.

Challenges of Scrapy:

Python 3.7+ is necessary for Scrapy.

4. Selenium

Selenium offers different open-source extensions and libraries to support web browser automation.

WebDriver APIs: Utilizes browser automation APIs made available by browser vendors for browser automation and web testing.

IDE (Integrated Development Environment): Is a Chrome and Firefox extension for creating test cases.

Grid: Make it simple to run tests on multiple machines in parallel.

Figure 3: Selenium’s toolkit for browser automation

Source: Selenium

Prerequisites:

Eclipse

Selenium Web Driver for Python

To learn how to setup Selenium, check Selenium for beginners.

Features of Selenium:

Provides testing automation features

Capture Screenshots

Provide JavaScript execution

Supports various programming languages such as Python, Ruby, chúng tôi and Java.

Benefits of Selenium:

Offers headless browser testing. A headless web browser lacks user interface elements such as icons, buttons, and drop-down menus. Headless browsers extract data from web pages without rendering the entire page. This speeds up data collection because you don’t have to wait for entire web pages to load visual elements like videos, gifs, and images.

Can scrape JavaScript-rich web pages.

Operates in multiple browsers (Chrome, Firefox, Safari, Opera and Microsoft Edge).

Challenges of Selenium:

Taking screenshots of PDFs is not possible.

5. Playwright

Playwright is an open-source framework designed for web testing and automation. It is maintained by Microsoft team.

Features of Playwright:

Three things are required to install Playwright:

Python

Pytest plugin

Required browsers

Benefits of Playwright:

Are capable of scraping JavaScript-rendered websites.

Takes a screenshot of either a single element or the entire scrollable page.

Challenges of Playwright:

It does not support data parsing.

6. Lxml

Lxml is another Python-based library for processing and parsing XML and HTML content. Lxml is a wrapper over the C libraries libxml2 and libxslt. Lxml combines the speed of the C libraries with the simplicity of the Python API.

Lxml installation: You can download and install the lxml library from Python Package Index (PyPI).

Requirements

Python 2.7 or 3.4+

Pip package management tool (or virtualenv)

Features of LXML:

Lxml provides two different API for handling XML documents:

lxml.etree: It is a generic API for handling XML and HTML. lxml.etree is a highly efficient library for XML processing.

lxml.objectify: It is a specialized API for handling XML data in Python object syntax.

Lxml currently supports DTD (Document Type Definition), Relax NG, and XML Schema schema languages.

Benefits of LXML:

The key benefit of lxml is that it parses larger and more complex documents faster than other Python libraries. It performs at C-level libraries, including libxml2 and libxslt, making lxml fast.

Challenges of LXML:

lxml does not parse Python unicode strings. You must provide data that can be parsed in a valid encoding.

The libxml2 HTML parser may fail to parse meta tags in broken HTML.

Lxml Python binding for libxml2 and libxslt is independent of existing Python bindings. This results in some issues, including manual memory management and inadequate documentation.

7. Urllib3

Python Urllib is a popular Python web scraping library used to fetch URLs and extract information from HTML documents or URLs.

urllib.request: for opening and reading URLs (mostly HTTP).

urllib.parse: for parsing URLs.

urllib.error: for the exceptions raised by urllib.request.

urllib.robotparser: for parsing chúng tôi files. The chúng tôi file instructs a web crawler on which URLs it may access on a website.

Urllib has two built-in Python modules including urllib2 and urllib3.

urllib2: Sends HTTP requests and returns the page’s meta information, such as headers. It is included in Python version 2’s standard library.

Figure 4: urllib2 sends request to retrive the target page’s meta information

Source: Urllib2

urllib3: urllib3 is one of the most downloaded PyPI (Python Package Index) packages.

Urllib3 installation: Urllib3 can be installed using pip (package installer for Python). You can execute the “pip install urllib3” command to install urllib in your Python environment. You can also get the most recent source code from GitHub.

Figure 5: Installing Urllib3 using pip command

Source: GitHub

Features of Urllib3:

Proxy support for HTTP and SOCKS.

Provide client-side TLS/SSL verification.

Benefits of Urllib3:

Urllib3’s pool manager verifies certificates when making requests and keeps track of required connection pools.

Urllib allows users to access and parse data from HTTP and FTP protocols.

Challenges of Urllib3:

It might be challenging than other libraries such as Requests.

8. MechanicalSoup

MechanicalSoup is a Python library that automates website interaction.

MechanicalSoup installation: Install Python Package Index (Pypi), then write “pip install MechanicalSoup” script to locate MechanicalSoup on PyPI.

Features of MechanicalSoup:

Mechanicalsoup uses BeautifulSoup (BS4) library. You can navigate through the tags of a page using BeautifulSoup.

Automatically stores and sends cookies.

Utilizes Beautiful Soup’s find() and find all() methods to extract data from an HTML document.

Allows users to fill out forms using a script.

Benefits of MechanicalSoup:

Supports CSS and XPath selectors. XPaths and CSS Selectors enable users to locate elements on a web page.

Challenges of MechanicalSoup:

MechanicalSoup is only compatible with HTML pages. It does not support JavaScript. You cannot access and retrieve elements on JavaScript-based web pages.

Does not support JavaScript rendering and proxy rotation. 

Further reading

Feel free to Download our whitepaper for a more in-depth understanding of web scraping:

If you have more questions, do not hesitate contacting us:

Gulbahar Karatas

Gülbahar is an AIMultiple industry analyst focused on web data collections and applications of web data.

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Top 7 Rpa Applications & Use Cases In Real Estate In 2023

Real estate and property management involve multiple data processing tasks, including management of documents, inventory, and other key processes (no pun intended), such as, procurement, accounting, reconciliation, etc.

These data-heavy, documented, and rules-based processes in real estate can reduce the productivity of employees and the business.

Thanks to Robotic Process Automation (RPA) technology, 70-80% of rules-based processes can be automated, thus making the real estate industry, which is ridden with rules-based workflows, ripe for automation. Delegating mundane tasks to bots can allow realtors to focus on more important tasks, such as closing deals, providing personalized support to home-buyers, and helping them find the best accommodation with respect to their budget and needs.

In this article, we discuss the top 7 use cases and applications of RPA in the real estate industry.

What is RPA in real estate?

RPA is the technology to automate processes that have a high degree of standardization and repetition rates. 

RPA’s ability to perform and automate tasks such as:

What are the applications and use cases of Robotic Process Automation in real estate?

We have spotted 60+ RPA use cases, and almost half of them applied to real estate since these processes include daily, back-office activities every business needs to perform.

Here are the common real estate processes RPA can automate:

Real Estate Operations 1. Tenant onboarding

A tenant’s onboarding process has various manual and time-consuming tasks that could result in a negative customer experience. The subsequent disillusionment might lead them to pass on the opportunity and sign a deal with a competing landlord.

RPA bots can be programmed to extract and process information to handle rule-based tasks in the tenant onboarding process. Specifically, they can:

Create a new tenant application

Run criminal background checks

Verify income, employment, and references

And approve or disapprove the applicant based on whether they’ve passed the aforementioned preliminary checks.

2. Payment reminders

Late payments are a common, repetitive, and emotionally taxing part of real estate management. Automating rent payment reminders include setting up a bot for checking incoming payments to verify the payee’s information, and sending email reminders to non-paying tenants.

3. Portfolio Management

Portfolio management, the same as traditional asset management, is the process of managing real estate assets to preserve, optimize, and increase their value. Real estate portfolio optimization is offloading underperforming properties and purchasing those that are in demand or have room (no pun intended) for growth.

Visibility into the specifics of a portfolio’s assets can make portfolio management more efficient and streamlined. For instance, RPA enables realtors to automatically list the sold-out/rented properties from the ERP systems, and update the data on multiple websites simultaneously to offer high visibility into the existing properties.

4. NAV calculations

The net asset value (NAV) is one of the useful metrics for assessing the value of a real estate investment trust (REIT). Net asset value (NAV) in private real estate investing is the total value of an asset, minus any outstanding debt and the cost of any fixed or planned capital expenses.

Real estate investors should understand NAV because asset prices are what drive current and future investor returns. For example, an increase in NAV correlates with an increase in distributable dividends to the investors who had invested in the property.

Real estate investors can automate some of the NAV calculation steps by using RPA solutions. NAV calculation consists of manual and labor-intensive steps such as collecting, validating, and processing market data and applying this to the funds to calculate a complete and accurate NAV.

For example, Maitland, an investment and fund administration company, automated the NAV processes for 500 of their 700 funds with an RPA solution1.

5. AML/KYC Compliance

RPA bots can validate existing customer data on transactions by extracting customer data from various internal ERP sources. Customer info can be verified autonomously or transferred to an employee for review. RPA also can automatically send emails with alerts to frontline staff requesting necessary KYC documentation.

RPA also minimizes human contact with sensitive data which reduces the probability of fraud and compliance issues. This allows a detailed audit in case issues arise.

See our articlea about:

Financial Operations 6. Accounts Payable (AP) / Accounts Receivable (AR) automation

With the further augmentation of RPA with machine learning and document extraction technologies such as Optical Character Recognition (OCR), businesses can automate most of AP and AR sub-processes, such as data verification, balance sheet forecasts, invoicing, and more.

7. Bank & Account Reconciliation

RPA can automate the extraction of bank statements from different banks, that the real-estate firm works with, in order to reconcile their account, and cross-match them with their general ledger entries.

RPA simplifies this process by uploading downloaded bank statements to a shared drive or financial application for account reconciliation.

For more on RPA

To learn more on RPA, feel free to read our comprehensive research on the topic:

To get a more in-depth look into RPA, download our RPA whitepaper below:

And if you still have questions on RPA applications in real estate, don’t hesitate to contact us:

If you feel like you would benefit from RPA in your business, you can check out our prioritized, comprehensive list of RPA vendors to choose the right RPA vendor for your business.

Sources

NAV calculation case study

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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Top 7 Conversational Ai Platforms In 2023 That You Must Try

Top 7 Conversational AI Platforms in 2023 that you must try to enhance your business.

Conversational artificial intelligence has the potential to change the way you provide customer support. This technology can simulate human-computer interactions. These platforms may be a game-changer for your customer care staff because of their clever features. However, to receive the top-tier help that AI can provide, you must first choose the top conversational AI platforms for your company. Conversational AI platforms have a wide range of corporate applications, including client acquisition and retention. It can assist you in providing a better customer experience and promptly and efficiently resolving client issues. 

Kore.ai:

Kore.ai is one of the top conversational AI platforms which was created with the needs of businesses in mind. Enterprises may use this platform to develop, test, produce, and deploy AI-enabled assistants. The chúng tôi platform has capabilities that improve the entire employee, customer, and agent experience. It has applications in a variety of industries, from media and entertainment to retail. The platform includes a multi-pronged NLP engine, supports over 30 channels, has a flexible deployment architecture, is easy to integrate with bespoke ML models and custom channels, and provides detailed statistics.  

SAP: 

With the aid of AI chatbots, this one of the top SAP conversational AI platforms helps you to automate numerous operations and improve customer service. Top-tier language technology and end-to-end bot development fuel the tool. You can even use Slack to install a bot. Your bot may evaluate text and examine crucial facts using SAP’s sophisticated natural language processing to improve your customer’s talking experience. Multiple languages are supported, and bots can switch between them in the middle of a conversation. The platform interfaces with SAP and non-SAP technologies, as well as providing detailed statistics to help you get the most out of your bots.  

HappyFox:

The bot solution for the live chat platform is a custom-built bot for enterprise enterprises. HappyFox Chatbot is designed to minimize your support volume by deflecting tickets. Their main goal is to assist your support crew in doing more with less. HappyFox and Zendesk, for example, can interface with conversational AI platforms. Tickets generated by artificial intelligence-driven discussions can still be escalated to your live agents in this way. Bots aren’t meant to take the place of agents; instead, they may address lower-priority issues so that your team can focus on the more difficult ones. Those that are interested can contact HappyFox for a quote.  

Clinc:

Clinc is of the top conversational AI platforms. This one of the top conversational AI platforms will help you understand customers as you’ve never understood them before. Clinc is best known for creating the most popular virtual assistant for banking self-service. Clinc’s impressive work in the space has been covered by publications such as Forbes, The New York Times, and Venture Beat. Clinc is powered by eight artificial intelligence engines that can process a user’s request from inquiry to the intelligent response. The tool includes powerful natural language processing (NLP) and conversation management features to ensure that conversations flow smoothly and make sense to the customer. You can even give your bots personalities to make sure they match the tone of your company. Because the firm uses a quote-based pricing strategy, potential consumers will need to contact them for additional information.  

Boost.ai:

Among the other top conversational AI platforms, chúng tôi is one of the most popular ones. chúng tôi is a solution designed for enterprises of all sizes. Self-learning AI on the platform can turn your website, chat logs, and outdated bots into a top-tier support crew. The no-code conversation builder from chúng tôi allows you to create templates for talks in different languages without having to know how to code. Its  Users may automate customer-facing procedures and workflows using Mindsay. By combining 

Sparkcentral:

All Android Smartphones Will Soon Be Able To Connect To Satellites

You can communicate from anywhere in the world if you can see even a small patch of sky. Francesco Grilli, the Qualcomm vice president in charge of satellite technologies, has made this commitment. He demonstrated how this technology would soon be available in Android smartphones at CES 2023. Thereby responding to Apple. Which in September 2023 with the release of its iPhone 14 launched the era of emergency satellite communication.

If Qualcomm trails Apple in the race, it is primarily due to Qualcomm’s later debut date for processors. Qualcomm typically introduces its SoCs at the end of the year. However, Qualcomm’s “delay” primarily pertains to the software rollout and launch of the services. The vast majority of high end Android devices this year that incorporate Snapdragon 8 Gen 2 CPUs are already compatible. But the choice of the satellite partner sets Qualcomm’s technology apart from Apple’s in a significant way.

The satellites connection of Android smartphones will be much better than iPhone

In contrast to Apple, who contracted with Globalsat, Qualcomm turned to American Iridium, another satellite expert. Who is unquestionably the field’s heavyweight in the industry. Most people who work in fields that need them to think creatively outside the box, such as mountaineers, humanitarians, explorers, journalists covering armed conflicts, and government officials, are likely to have a satellite phone. It is often an Iridium-based device because of this network’s main strength: its global reach.

A device compatible with the Iridium network can successfully send and receive messages from the North Pole to Point Nemo in the Pacific Ocean as soon as a patch of sky is available – bidirectionality which will also be on the agenda with smartphones. The Globalsat network is not like that. The two networks’ technical architecture is to blame for this. Iridium is a constellation with inter satellite communications. Whereas Globalsat relies on ground relays (there are several dozen on the earth).

Sattelite connection will be available for all Qualcomm smartphones

Gizchina News of the week Strengths of Apple: integration and investments

As we’ve seen, Globalstar does not provide the same level of comprehensive coverage as Iridium. The network is secondly dependent on a small number of ground stations. Because the satellite industry, which includes Iridium, Inmarsat, Globalstar, and Thuraya, is small and doesn’t produce much revenue. Without the “debauchery” side that an actor like Space X can portray, all launches are controlled. Apple is completely aware of everything. Without a doubt, this is the reason the American giant has chosen to improve the network. By digging further into its pockets.

Therefore, since the release of the iPhone 14, Apple has been quite insistent in its marketing about the feature. To discuss its investment in the system. Thus, the Americans will invest 450 million dollars over the course of five years to strengthen the ground station network. In the beginning in the states of Hawaii, Alaska, Florida, Nevada, or Puerto Rico in the United States (first market where the service was deployed). Since so few people actually require Iridium’s global coverage, many American states continue to be sparsely populated, untamed, and occasionally lacking in adequate network infrastructure. Thus, it appears that Apple’s answer is already appropriate for a larger audience.

Last but not least, Apple will also stand out on the integration side. Because the service is (as usual with Apple! ), planned out from A to Z. The ease of signing up for a protection plan when the time comes. Right now it’s free for two years, and time will tell what Apple has chosen, etc. Pre-recorded messages in the terminal (which automatically encompass GPS position) to software integration, etc. The American has everything set up already.

Qualcomm’s Android partners will need to start from scratch to develop not only a software offer. But also a technical and commercial offer that is tailored to each country. Where the devices are sold if they want to compete with Apple. The Achilles heel of Android devices is typically their finishes. Hope Qualcomm has already set the stage for its partners; if not. It will likely be necessary to wait a little while for its solution. Which is superior in terms of space, to truly challenge Apple’s.

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