Snapchat announced investments in ML and automation, at the 2024 IAB NewFronts event on Wednesday, to facilitate the creation of AR try-on experiences.

Building on successful collaborations with brands like Amazon and Tiffany & Co., Snapchat is reducing the time it takes to develop these features, allowing brands to quickly change their existing 2D product catalogues into interactive try-on experiences within the app.

The introduction of generative AI technology enables brands to create custom AR ad experiences. Using a simple text or image prompt, brands can generate a unique machine-learning model that adds realistic face effects to Snapchat Lenses. These AI-powered Lenses can then be incorporated into AR ads on the platform.

The company is also introducing AR Extensions, allowing advertisers to seamlessly integrate AR Lenses and filters directly into all its ad formats. This includes Dynamic Product Ads, Snap Ads, Collection Ads, Commercials, and Spotlight Ads.

The launch of these new tools follows Snapchat’s recent Q1 2024 earnings report, which revealed a 21% year-over-year revenue increase to $1.195 million. This growth is largely attributed to improvements made to the company’s advertising platform. 

Furthermore, Snapchat reports an 85% year-over-year increase in the number of small and medium-sized businesses advertising on the platform.

Beyond advertising, Snapchat is also diversifying its content offerings with the launch of the “Snap Sports Network” channel. This unique platform will focus on showcasing unconventional sports like dog surfing, extreme ironing, and water bottle flipping. 

User-generated content will be a key component, alongside scripted content hosted by popular Snapchat personalities (“Snap Stars”).

Additionally, Snapchat is expanding its partnership with Live Nation. A new “Snap Nation Public Profile” will give exclusive behind-the-scenes content from concerts. 

Live Nation concert stories curated by Snapchat will feature public user posts, further enriching the concert experience for fans.

So, why don’t we explore practical applications of AI and ML that businesses can leverage to achieve success? Let’s dive in:

1. Enhanced Customer Experience

AI and ML technologies can significantly enhance the customer experience by personalizing interactions and predicting customer behavior. By analyzing vast amounts of data, businesses can gain insights into customer preferences, purchasing patterns, and sentiment analysis. This enables them to deliver tailored recommendations, targeted marketing campaigns, and proactive customer support, ultimately fostering customer loyalty and satisfaction.

2. Intelligent Automation

Automation powered by AI and ML can streamline business processes, reduce manual labor, and improve operational efficiency. Tasks such as data entry, report generation, and repetitive workflows can be automated, freeing up valuable time for employees to focus on more strategic initiatives. Intelligent automation also reduces errors and enhances accuracy, leading to higher productivity and cost savings.

3. Predictive Analytics

AI and ML algorithms excel at analyzing data and identifying patterns that humans might overlook. By leveraging predictive analytics, businesses can make data-driven decisions and anticipate future trends, enabling them to stay ahead of the competition. Predictive analytics can be applied to various areas, such as demand forecasting, inventory management, pricing optimization, and risk assessment, empowering businesses to make informed choices and optimize outcomes.

4. Fraud Detection and Security

AI and ML algorithms are adept at detecting anomalies and identifying fraudulent activities. These technologies can be employed to detect patterns of fraudulent transactions, cybersecurity threats, or unauthorized access attempts. By continuously monitoring and analyzing data in real-time, businesses can strengthen their security measures and protect sensitive information, ensuring a safe and secure environment for both customers and internal operations.

5. Intelligent Data Insights

The ability to extract actionable insights from vast amounts of data is a key advantage of AI and ML. These technologies can process and analyze structured and unstructured data from multiple sources, enabling businesses to uncover hidden patterns, trends, and correlations. This valuable information can guide strategic decision-making, drive innovation, and identify untapped market opportunities, leading to business growth and competitive advantage.

6. Smart Resource Allocation

AI and ML algorithms can optimize resource allocation by analyzing historical data, market conditions, and operational constraints. This enables businesses to make informed decisions regarding budget allocation, workforce management, and inventory optimization. Through optimization of resource allocation, businesses can minimize costs, improve efficiency, and maximize return on investment.

In conclusion, AI and ML technologies offer immense potential for businesses seeking growth and success. By embracing these technologies and applying them in practical ways, such as enhancing customer experience, enabling intelligent automation, leveraging predictive analytics, strengthening security measures, gaining valuable data insights, and optimizing resource allocation, businesses can gain a competitive edge and thrive in today’s digital era. 

Embrace the power of AI and ML, and unlock new possibilities for your business’s growth and prosperity.

From virtual reality to artificial intelligence, cloud-based storage, automated analytics, AI-driven property management, data-driven insights and virtual tours, the Real Estate industry is adopting innovative technologies that are revolutionizing the way we view, interact, and transact with our properties. 

With these advancements, the Real Estate industry is poised to become more efficient, cost-effective, and customer-centric than ever before. Join us as we explore the technologies that are making this revolutionary change possible.

In this new era of real estate, technologies like artificial intelligence, the Internet of Things (IoT), machine learning, and blockchain are all playing a part in transforming the industry. With these tools, agents, brokers, and investors can complete processes faster, make smarter decisions, and reduce overhead costs.

To start, artificial intelligence (AI) is making it easier for real estate agents and brokers to manage multiple properties. AI-enabled applications are helping agents and brokers identify potential buyers and sellers, as well as generate leads and analyze the market. AI can also be used to automate the property management process, helping agents and brokers reduce paperwork and streamline operations.

The Internet of Things (IoT) is also making an impact on the real estate industry. IoT-enabled devices are being used to improve the efficiency of building management systems, monitor energy use, and detect problems before they become major issues. IoT is also making it easier to manage remote properties, as well as to monitor tenant activity.

In addition to AI and IoT, machine learning is equally having an impact on the real estate industry. Machine learning algorithms can be used to analyze large datasets and make better decisions on behalf of agents and brokers. For instance, machine learning algorithms can be used to identify patterns in the market and suggest effective strategies for pricing and marketing.

Finally, blockchain is also making its mark on the real estate industry. Blockchain technology is enabling the secure transfer of data and the secure storage of documents, making it easier and safer to manage records. It is also making it possible to create smart contracts, helping agents and brokers streamline the process of renting or selling a property.

The real estate revolution is transforming the industry and making it more efficient and profitable. New technologies like AI, IoT, machine learning, and blockchain are all helping to make the process of managing real estate more efficient and secure. It is an exciting time for the industry and those who are investing in it.

Ultimately, these technologies are creating a more efficient, streamlined real-estate industry that is benefiting both buyers and sellers.

By leveraging data-driven insights, they are making the entire process more cost-effective. Moreover, they are also providing new opportunities for investors to tap into lucrative markets.

As a result, real estate is poised to become an even more valuable asset in the future. Professionals in the industry must stay abreast of the latest developments in order to make the most of this revolution.

With exponentially more ransomware incidents being reported than there are skilled cybersecurity professionals available, progressive businesses are looking to Artificial Intelligence (AI) and Machine Learning (ML) to close the gap.

Every day more and more people and businesses are held to ransom as exposed vulnerabilities are exploited by criminals.

Even those with robust cybersecurity strategies in place are concerned by the sheer number of business attacks, which increase in number every year.

The cost of attacks was estimated to rise to USD$10 trillion annually by 2025 according to a 2020 report, and may yet exceed that amount.

Given the stark reality of everyone connected to the internet potentially becoming a victim of a cyberattack, managing cyber threats manually and still having time to actually do business is no longer possible, says Patrick Evans, Chief Executive Officer of SLVA Cybersecurity. 

“Protecting all end-points, integrations, APIs and every other threat vector is, quite literally, an insurmountable task. A staggering 93 percent of companies can be penetrated by cybercriminals; the consequences of which to the unprepared are dire indeed. Consequences that span from service disruptions, the holding of information and systems to ransom, through to destruction of physical infrastructure which, beyond the inconvenience, the financial and reputational implications, and potential threat to life, can easily result in the total loss of an organisations ability to remain in business,” explains Evans.

This is where artificial intelligence (AI) and machine learning (ML), both of which are being used with great success in reliable and resource saving robotic process automation, become so interesting for the management of our overloaded and under resourced cyber threat environments. Machines have always processed data faster than humans can, but not always any better. Which is why ML that can use the most proficient and effective techniques to analyse massive amounts of data is becoming mainstream and widely used today. “More importantly, as the latest developments in AI now start to reliably deploy systems that can start up and fully learn its environment in the way a skilled and experienced human does, AI can now deliver reliable and repeatable analytics with immediate accurate and automated responses for those the high volume repetitive security event monitoring tasks that cannot retain or even attract, the level of human skills required for reliable results.” says Evans.

“It goes further.  AI/ML can operate at scale which was not possible before.  What this means is that for the first time, one can continually ingest and analyse data from all relevant cyber security and IT tools to present a unified and cohesive view of an organisation’s investments in real time.  Now enterprises can report cyber risk in business terms and in rand terms, which is traceable to underlying operational reality, which delivers multiple benefits to any organisation.

This use of AI has long helped alleviate the skills gap throughout the global ICT market by automating highly manual processes, aggregating feedback, and taking over massive and mundane tasks to free up humans to focus on implementation and further research.

This IT and cyber skills shortage is even more stark in South Africa where local demand far surpasses even international supply. AI tools however do not just provide a replacement for missing skills, they have also become critical teaching components in growing new cybersecurity and risk skills.

Emigration and remote work arrangements now mean local employers compete for local talent against international corporates with deeper pockets.

“AI and ML build not only build up a database of vulnerable threat vectors and then based on discovery can continually test and learn new ways of attacking systems, they can also use their understanding of how to manage threats to teach the next generation of cyber risk managers. They do this 24/7/365, and as a result, are extremely effective,” he says.

“Bespoke cybersecurity solutions that leverage AI and ML are easily the most effective testing and discovery engine for companies looking to defend their systems. Key insights provided by the ongoing threat detection systems allow highly skilled and scarce resources to prioritise their time in more meaningful ways,” Evans adds.

With the average cost of a ransomware attack now standing at USD$1,85 million, every sector in every industry is at risk. While breaches at large firms make headlines, Evans cautions that small and medium-sized entities are often not aware of the extra risk they carry and are often an easier target for hackers because of SMEs’ lack of resources and security expertise. And it’s not just tech companies being attacked. Any business running a web application and those with operations in education, manufacturing, and finance are finding themselves to be frequent and popular targets for criminals.

Says Evans: “It’s simply not feasible to address all your cybersecurity requirements with a single vendor let alone a single team or a single person. The landscape is far too vast and ever-expanding for that.

Considering the current environment where skills are scarce, threats are multiplying, and businesses must contend with the very real possibility of complete closure because of cybercrime, the only answer is the adoption of smart ML and AI tools aligned to the threats specific to your business that will leverage on others understanding to manage the most aggressive threat environments you can expect.

Artificial intelligence and machine learning are not silver bullets that can just be used without thought, but in the hands of cybersecurity and IT professionals are tools that can be readily and reliably deployed to bolster existing cybersecurity solutions that allow any business to resiliently avoid damage from the all but inevitable cyber attacks that are today’s reality.”