2 posts tagged with "artificial intelligence"

Whether it's identifying faces in your images, converting spoken words into text, or anticipating your next online buy, artificial intelligence (AI) frequently seems like magic. Behind the scenes, however, artificial intelligence is more about math, patterns, and logic than it is about magic. Let's solve the puzzle of artificial intelligence and illustrate its fundamentals with approachable examples.

What Is AI?#

Fundamentally, artificial intelligence (AI) is the study of programming machines to carry out operations like learning, reasoning, and problem-solving that often call for human intelligence. The majority of the magic occurs in Machine Learning (ML), a subset of AI; it is the process of teaching machines to learn from data instead of directly programming them.

Learning Like Humans Do#

Imagine teaching a child to recognize cats:

• You display cat images and declare, "This is a cat."
• The kid notices patterns, such as the fact that cats have whiskers, hair, and pointed ears.
• The child makes educated predictions about whether or not new photographs depict cats, getting better with feedback.

Machine Learning works similarly but uses data and mathematical models instead of pictures and intuition.

How Machines Learn: A Simple Recipe#

1. Data Is the Foundation#

Data collection is the initial step. To create a system that can identify spam emails, for instance:

• Gather spam emails, such as "You won $1,000,000!."
• Gather emails that aren't spam, such work emails or private notes.

2. Look for Patterns#

The system looks for patterns in the data using statistics. For example:

• Spam filters often have certain keywords ("free," "winner," "urgent").
• Non-spam emails are less likely to use these terms frequently.

3. Build a Model#

The model instructs the machine on how to determine whether an email is spam, much like a recipe. In essence, it is a collection of mathematical principles developed with the aid of algorithms such as:

• Decision Trees: "If the email contains 'free,' it's likely spam."
• Probability Models: "Emails with 'urgent' have an 80% chance of being spam."

4. Test and Improve#

After the model is constructed, its performance is evaluated using fresh data. The model is modified if it makes errors; this process is known as training.

Relatable Examples of Machine Learning in Action#

1. Predicting the Weather#

AI forecasts tomorrow's weather by analyzing historical meteorological data, such as temperature, humidity, and wind patterns.

• The Math: It uses statistics to find correlations (e.g., "If humidity is high and pressure drops, it might rain").

2. Recommending Movies#

Your watching history is used by services like Netflix to predict what you'll like next.

• The Calculation: It uses an algorithm known as Collaborative Filtering to compare your choices with those of millions of other users. It's likely that you will enjoy a film if someone with similar preferences did.

3. Translating Languages#

AI systems like Google Translate convert languages by learning patterns in how words and phrases map to each other.

• The Math: It uses a model called a Neural Network, which mimics how the brain processes information, breaking sentences into chunks and reassembling them in another language.

Breaking Down AI Techniques#

1. Supervised Learning#

The machine is comparable to a pupil and a teacher. The machine learns from the labeled data you provide it (for example, "This is a cat, this is not").

• Emails marked as "spam" or "not spam" are used to teach Spam filters, for instance.

2. Unsupervised Learning#

The machine gets no labels—it just looks for patterns on its own.

• Example: Customer segmentation in e-commerce based on buying habits without predefined categories.

3. Reinforcement Learning#

Through trial and error, the computer gains knowledge, earning rewards for right acts and punishments for incorrect ones.

• Example: Teaching a robot to play chess by rewarding wins and penalizing losses.

Why AI Is Just Math at Scale#

Here's where the math comes in:

• Linear Algebra: Models often manipulate large tables of numbers (called matrices).
• Probability: Aids machines in handling uncertainty, such as forecasting if it will rain tomorrow.
• Calculus: Fine-tunes models by optimizing their performance, adjusting parameters to reduce errors.

Humans are naturally adept at identifying patterns in data, such as identifying weather trends or identifying a buddy in a crowd, despite the fact that these ideas may seem complicated.

But AI Feels So Smart! Why?#

The secret to AI's power isn't just the math—it's the scale. Machines can analyze millions of data points in seconds, uncovering patterns far too subtle for humans to notice.

• Example: In healthcare, AI can detect early signs of diseases in medical images with accuracy that complements doctors' expertise.

AI Is Not Perfect#

Despite its power, AI has limitations:

• Garbage In, Garbage Out: If you train it with bad data, it will give bad results.
• Bias: Biases from the training data can be inherited by AI (e.g., under-representing some populations). Find out more about bias in AI.
• Lack of Understanding: AI does not "think" like humans; it recognizes patterns but does not fully comprehend them.

Conclusion#

AI may appear magical, yet it is based on mathematical principles and powered by data. The next time you see a product recommendation, hear a virtual assistant, or see AI in action, remember that it is not magic—it is a sophisticated combination of math, logic, and human intelligence. And the best part? Anyone can learn how it works. After all, understanding the mathematics behind the curtain is the first step toward mastering the magic for yourself.

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Mobile Edge Computing (MEC) can aid is with real estate property browsing. MEC can provide a two-fold answer. Most buyers look at many residences and don't make decisions without viewing them. Engaging Mobile Edge Computing (MEC) applications like augmented reality (AR) and virtual reality (VR) demonstrate strong opportunities to connect the external and simulated worlds, whether it's putting a virtual couch in your sitting room as part of an interactive retail setting or allowing forecasting refurbishment steered by actual data as well as a layering of step-by-step graphic guidelines. As an element of synchronized and safe processes, the objective is to allow all sides to see what other sees. Combining smartphones and tablets, iPads, and smartwatches with virtual collaborative technologies redefine learning and allow product specialists to help from a distance (Ambrose and Shen, 2021). The goal is to make the distant assessment, replacement, and service of existing goods more efficient.

AR (augmented reality) and VR (virtual reality) are still considered specialized innovations which have yet to be widely accepted. A lot of it comes down to the issues that edge computing can now solve. Following the commercial release of 5G, AR (augmented reality) and VR (virtual reality) encompasses a slew of innovative application cases that, when combined by the edge of the network, will provide significant value to the sector and businesses. Applying virtual layers to live sights is what augmented reality is all about. It can be performed with a device, but in business, wearable technology is much more probably to be used. VR is total absorption in a digital perspective that requires the use of a set of glasses that block the user's view of the world surrounding them (Gerasimova, 2019).

The real estate sector is likely to be transformed by this technology, which some belief would make property hunting more effective. It can help purchaser's picture houses in progress and alleviate the stress of moving to the new location or purchasing from overseas.

What role does Edge and AR play in wooing customers in property hunting?#

With AR (augmented reality), real estate reaches new heights in terms of providing consumers with a more efficient and interesting visual journey. Retailers may now transport them to any destination they like. Offer visitors a digital tour to relieve the stress of having to figure out road signs and building numbers while travelling. People will also have a complete image of the place after they have had the opportunities to explore it. Aside from the ease, it provides to property buyers, it also assists real estate brokers in other ways. Augmented Reality may also be used for branding and advertising (Lang and Sittler, 2012).

The following are some of the marketing aspects of augmented reality for property investment:

• More dynamic print catalogues and large boards are being developed.
• Spatial that really can help for-sale properties in real-time.
• Get an interactive function in the app so a potential buyer may reach out to the retailer right away.
• A larger audience

How to Use Virtual Reality in Property Hunting?#

Virtual reality performs a vital part in the property market, from real estate development to housing developments. Let's take a look at several ways that may use virtual reality property hunting:

• Guided Visits: Property hunters, on the whole, compile a list of properties they wish to see and then go to the locations. Some residences are nearby, while some are on the periphery. As a result, planning a visit and narrowing down a list of prospective homes becomes physiologically and psychologically demanding. VR in the housing market efficiently overcomes all of these issues (Pleyers and Poncin, 2020).

• Participatory Visits: Participatory visits are growing in popularity these days. The key difference between supervised and participatory trips would be that active trips allow property hunters to tap on the display and zoom in on certain areas of the property.

• Virtual Staging: The term "virtual staging" refers to the technique of electronically furnishing vacant places. Simply defined, VS is a property investment internet marketing tactic that lets customers see themselves in completely furnished homes.

• Communication: Modern residences and ultra-luxury homes now provide a variety of public utilities. While such products and services provide convenience, they may also be perplexing sometimes.

The Benefits of Edge-VR in Property Hunting:#

• Time and money-saving.
• Creates an emotional bond.
• Profits increased.
• Experimentation is simple.
• Reach Out to a Larger Audience

What is the difference between VR and AR?#

AR and VR are both disruptive technologies, they have some significant distinctions:

Conclusion for Edge and AR#

Several businesses that are willing to embrace augmented reality are unable to do so due to limitations in their capacity to exchange data on the cloud. Companies may utilise graphical tools and applications like Zoom or Microsoft Exchange for normal communication, but they can't use the same cloud-based solutions for critical organisational activities like learning, support, or technical access because of data security and privacy ownership issues. AR and VR are on the verge of allowing participants to take their immersive experience with others, which is something that most people like about property hunting. In terms of what's feasible, both AR and VR are advancing at breakneck speed (Deaky and Parv, 2017). It's nearly a perfect match for property hunting.

To know the benefits of Edge Computing please read: Differentiation Between Edge Computing and Cloud Computing