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The Role of Artificial Intelligence in Marketing and Customer Service



Role of Artificial Intelligence in Marketing and Customer Service

The advent of artificial intelligence (AI) has revolutionized the way businesses operate and interact with their customers. In particular, the marketing and customer service field has seen a significant shift toward incorporating AI technologies. From chatbots and virtual assistants to machine learning algorithms, AI is utilized in various ways to improve customer engagement, increase efficiency and drive sales.

One of the most prominent applications of AI in marketing and customer service is chatbots and virtual assistants. These computer programs are designed to mimic human conversation and can provide quick and accurate responses to customer inquiries 24/7. This is especially beneficial for businesses that operate globally, as chatbots can handle multiple languages and time zones. Implement chatbots in your business with the expertise of professionals at Managed IT Services Sacramento.

Read this blog on how artificial intelligence revolutionizes customer service and can be leveraged in marketing strategies to impact your customer experience journey.

What is AI in Marketing?

Artificial intelligence marketing uses AI software to automatically create, optimize, and market products using computer algorithms. AI marketing intelligence can help reduce customer service workload by automating tasks. As a result, customer service representatives can focus on providing exceptional customer experience instead of repetitive manual tasks. In addition, it can help identify customer needs and preferences. With the use of artificial intelligence, customer analytics, and machine learning, marketing teams can quickly identify customer needs and develop marketing strategies that are relevant and tailored to them.

Marketing and AI can help improve customer retention rates. By using artificial intelligence in marketing automation strategies, marketers can personalize campaigns and email content for customers based on their behavior or past interactions with the brand. This personalization helps retain customers and increase their engagement with the brand. In addition, AI marketing can help resolve customer complaints quickly and efficiently. With the use of artificial intelligence in customer data analytics and predictive modeling, a marketer’s team can analyze a customer’s data to determine potential problems and suggest possible solutions easily without having to take similar actions across many customers repeatedly.

6 Benefits of AI in Marketing and Customer Service

  1. Automated Image Recognition

Artificial intelligence (AI) has the potential to automate customer service processes and provide valuable data to help organizations improve customer experience. For example, it can identify customer profiles, track customer interactions, and predict customer needs. This information can help organizations tailor customer service interactions to meet customers’ needs better. Additionally, artificial intelligence in marketing campaigns can help companies target a specific customer demographic or build a more personalized marketing strategy.

By using artificial intelligence in marketing campaigns, companies can target a specific customer demographic or build a more personal marketing strategy. Overall, artificial intelligence has the potential to automate a range of customer service tasks and provide valuable data that helps organizations improve their customer experience.

  1. Improved PPC Advertising

AI-enabled PPC campaigns have the potential to help a marketing department improve customer service by predicting and managing customer interactions. For example, artificial intelligence can help a marketing team identify and qualify leads automatically, send email campaigns, and conduct telephonic interviews. This technology can also automate the process of identifying and allowing potential customers.

AI-enabled PPC campaigns can monitor and analyze customer sentiment and engagement, which can help a marketing team improve its targeting strategies over time. By using artificial intelligence in PPC campaigns, a marketing team can save a lot of time and money while simultaneously improving customer experience.

  1. Chatbot-based Customer Support

Chatbots are computer programs that simulate human conversation and can provide customer support. AI-powered chatbot customer support can be customized to give a personal experience for each customer. Chatbot customer support typically involves using a chatbot to handle complaints, inquiries, and support requests. In addition, chatbots can be integrated with CRM systems to automate customer interactions. It allows businesses to quickly and efficiently analyze customer data and response patterns for insights that can help improve customer experience and satisfaction.

Chatbots are a valuable tool for customer engagement, providing a more personal experience than a chatbot powered by a CRM system alone. Some examples of chatbot-based customer support include chatbot-based email support, chatbot-based chat support, chatbot-based live chat support, and chatbot-based social media support. Chatbots have the potential to revolutionize the digital age by using artificial intelligence customer service to interact with customers naturally.

  1. Better Customer Relationships & Real-Time Personalization

Artificial intelligence (AI) has the potential to revolutionize customer service by automating tasks and personalizing the customer experience. AI can help businesses improve customer relations by automating customer service tasks like chat support, email responses, and analytics.

In addition, by using artificial intelligence, companies can personalize customer service experiences by understanding a customer’s preferences and history. This allows companies to provide more relevant and personalized services to help customers stay loyal and recommend your business to their friends. By using artificial intelligence in customer service, businesses can save valuable time and resources while providing a better customer experience. As a result, customers are more likely to remain loyal to your company and recommend it to their friends.

  1. Assisting Customers in Make Decisions

Customer service through artificial intelligence (AI) is a valuable tool to help customers make informed decisions quickly. AI can assist customers with customer service tasks, such as responding to customer queries and issuing refunds. In addition, with the help of AI, customer service agents can be freed up to focus on other tasks, such as monitoring customer satisfaction levels and adjusting services accordingly. 

AI can also provide real-time updates on product availability and inventory levels. In addition to automating customer service tasks, artificial intelligence can help employees identify customer trends and recommend better service strategies. It helps them identify customer needs and develop tailored strategies for each customer.

Finally, AI can help employees monitor customer satisfaction levels and adjust services accordingly. By using artificial intelligence in customer service, businesses can experience a significant boost in efficiency and profitability.

  1. Personalized User Experiences

Customer service is becoming a field where artificial intelligence (AI) plays a significant role. AI can help create personalized customer experiences by understanding the customer’s preferences and past behavior. As a result, it can help customers get a good experience when using a product or service and experience a higher level of satisfaction with that experience. AI can also help reduce customer service response time by automating processes. For example, it can identify customer complaints more efficiently using machine learning. This technology allows analyzing data to determine if a customer has a legitimate complaint and, thus, can prevent customer service agents from spending time on false positives.

In addition, AI can help agents detect and prevent fraudulent or unethical behavior using intelligence-based analytics tools. With this technology, customer service teams can be better equipped to identify patterns of problematic customers and take appropriate action to address their needs as quickly as possible. Lastly, AI can help improve customer service interactions by providing feedback to agents using chatbots or virtual assistants. 


AI (Artificial Intelligence) is becoming an increasingly important tool in marketing and customer service. For example, AI-powered chatbots and virtual assistants can provide quick and accurate responses to customer inquiries, while machine learning algorithms can analyze customer data and make personalized recommendations. Additionally, AI can be used to optimize marketing campaigns and improve targeting. However, while AI can potentially improve customer engagement and sales significantly, it is essential to consider the ethical implications of using AI in these areas and ensure that data privacy and security are protected.

Post courtesy: George Passidakis, Director of Sales and Marketing at Apex Technology Management

Artificial Intelligence

Snowflake Launches Arctic: The Most Open, Enterprise-Grade Large Language Model



Snowflake generative ai

Snowflake (NYSE: SNOW), the Data Cloud company, today announced Snowflake Arctic, a state-of-the-art large language model (LLM) uniquely designed to be the most open, enterprise-grade LLM on the market. With its unique Mixture-of-Experts (MoE) architecture, Arctic delivers top-tier intelligence with unparalleled efficiency at scale. It is optimized for complex enterprise workloads, topping several industry benchmarks across SQL code generation, instruction following, and more. In addition, Snowflake is releasing Arctic’s weights under an Apache 2.0 license and details of the research leading to how it was trained, setting a new openness standard for enterprise AI technology. The Snowflake Arctic LLM is a part of the Snowflake Arctic model family, a family of models built by Snowflake that also include the best practical text-embedding models for retrieval use cases.

“This is a watershed moment for Snowflake, with our AI research team innovating at the forefront of AI,” said Sridhar Ramaswamy, CEO, Snowflake. “By delivering industry-leading intelligence and efficiency in a truly open way to the AI community, we are furthering the frontiers of what open source AI can do. Our research with Arctic will significantly enhance our capability to deliver reliable, efficient AI to our customers.”

Arctic Breaks Ground With Truly Open, Widely Available Collaboration
According to a recent report by Forrester, approximately 46 percent of global enterprise AI decision-makers noted that they are leveraging existing open source LLMs to adopt generative AI as a part of their organization’s AI strategy.1 With Snowflake as the data foundation to more than 9,400 companies and organizations around the world2, it is empowering all users to leverage their data with industry-leading open LLMs, while offering them flexibility and choice with what models they work with.

Now with the launch of Arctic, Snowflake is delivering a powerful, truly open model with an Apache 2.0 license that permits ungated personal, research, and commercial use. Taking it one step further, Snowflake also provides code templates, alongside flexible inference and training options so users can quickly get started with deploying and customizing Arctic using their preferred frameworks. These will include NVIDIA NIM with NVIDIA TensorRT-LLM, vLLM, and Hugging Face. For immediate use, Arctic is available for serverless inference in Snowflake Cortex, Snowflake’s fully managed service that offers machine learning and AI solutions in the Data Cloud. It will also be available on Amazon Web Services (AWS), alongside other model gardens and catalogs, which will include Hugging Face, Lamini, Microsoft Azure, NVIDIA API catalog, Perplexity, Together AI, and more.

Arctic Provides Top-Tier Intelligence with Leading Resource-Efficiency
Snowflake’s AI research team, which includes a unique composition of industry-leading researchers and system engineers, took less than three months and spent roughly one-eighth of the training cost of similar models when building Arctic. Trained using Amazon Elastic Compute Cloud (Amazon EC2) P5 instances, Snowflake is setting a new baseline for how fast state-of-the-art open, enterprise-grade models can be trained, ultimately enabling users to create cost-efficient custom models at scale.

As a part of this strategic effort, Arctic’s differentiated MoE design improves both training systems and model performance, with a meticulously designed data composition focused on enterprise needs. Arctic also delivers high-quality results, activating 17 out of 480 billion parameters at a time to achieve industry-leading quality with unprecedented token efficiency. In an efficiency breakthrough, Arctic activates roughly 50 percent less parameters than DBRX, and 75 percent less than Llama 3 70B during inference or training. In addition, it outperforms leading open models including DBRX, Mixtral-8x7B, and more in coding (HumanEval+, MBPP+) and SQL generation (Spider), while simultaneously providing leading performance in general language understanding (MMLU).

Snowflake Continues to Accelerate AI Innovation for All Users
Snowflake continues to provide enterprises with the data foundation and cutting-edge AI building blocks they need to create powerful AI and machine learning apps with their enterprise data. When accessed in Snowflake Cortex, Arctic will accelerate customers’ ability to build production-grade AI apps at scale, within the security and governance perimeter of the Data Cloud. 

In addition to the Arctic LLM, the Snowflake Arctic family of models also includes the recently announced Arctic embed, a family of state-of-the-art text embedding models available to the open source community under an Apache 2.0 license. The family of five models are available on Hugging Face for immediate use and will soon be available as part of the Snowflake Cortex embed function (in private preview). These embedding models are optimized to deliver leading retrieval performance at roughly a third of the size of comparable models, giving organizations a powerful and cost-effective solution when combining proprietary datasets with LLMs as part of a Retrieval Augmented Generation or semantic search service.

Snowflake also prioritizes giving customers access to the newest and most powerful LLMs in the Data Cloud, including the recent additions of Reka and Mistral AI’s models. Moreover, Snowflake recently announced an expanded partnership with NVIDIA to continue its AI innovation, bringing together the full-stack NVIDIA accelerated platform with Snowflake’s Data Cloud to deliver a secure and formidable combination of infrastructure and compute capabilities to unlock AI productivity. Snowflake Ventures has also recently invested in Landing AI, Mistral AI, Reka, and more to further Snowflake’s commitment to helping customers create value from their enterprise data with LLMs and AI.

Comments On the News from AI Experts
Snowflake Arctic is poised to drive significant outcomes that extend our strategic partnership, driving AI access, democratization, and innovation for all,” said Yoav Shoham, Co-Founder and Co-CEO, AI21 Labs. “We are excited to see Snowflake help enterprises harness the power of open source models, as we did with our recent release of Jamba — the first production-grade Mamba-based Transformer-SSM model. Snowflake’s continued AI investment is an important factor in our choosing to build on the Data Cloud, and we’re looking forward to continuing to create increased value for our joint customers.”

“Snowflake and AWS are aligned in the belief that generative AI will transform virtually every customer experience we know,” said David Brown, Vice President Compute and Networking, AWS. “With AWS, Snowflake was able to customize its infrastructure to accelerate time-to-market for training Snowflake Arctic. Using Amazon EC2 P5 instances with Snowflake’s efficient training system and model architecture co-design, Snowflake was able to quickly develop and deliver a new, enterprise-grade model to customers. And with plans to make Snowflake Arctic available on AWS, customers will have greater choice to leverage powerful AI technology to accelerate their transformation.”

“As the pace of AI continues to accelerate, Snowflake has cemented itself as an AI innovator with the launch of Snowflake Arctic,” said Shishir Mehrotra, Co-Founder and CEO, Coda. “Our innovation and design principles are in-line with Snowflake’s forward-thinking approach to AI and beyond, and we’re excited to be a partner on this journey of transforming everyday apps and workflows through AI.”

“There has been a massive wave of open-source AI in the past few months,” said Clement Delangue, CEO and Co-Founder, Hugging Face. “We’re excited to see Snowflake contributing significantly with this release not only of the model with an Apache 2.0 license but also with details on how it was trained. It gives the necessary transparency and control for enterprises to build AI and for the field as a whole to break new grounds.”

“Lamini’s vision is to democratize AI, empowering everyone to build their own superintelligence. We believe the future of enterprise AI is to build on the foundations of powerful open models and open collaboration,” said Sharon Zhou, Co-Founder and CEO, Lamini. “Snowflake Arctic is important to supporting that AI future. We are excited to tune and customize Arctic for highly accurate LLMs, optimizing for control, safety, and resilience to a dynamic AI ecosystem.”

“Community contributions are key in unlocking AI innovation and creating value for everyone,” said Andrew Ng, CEO, Landing AI. “Snowflake’s open source release of Arctic is an exciting step for making cutting-edge models available to everyone to fine-tune, evaluate and innovate on.”

“We’re pleased to increase enterprise customer choice in the rapidly evolving AI landscape by bringing the robust capabilities of Snowflake’s new LLM model Arctic to the Microsoft Azure AI model catalog,” said Eric Boyd, Corporate Vice President, Azure AI Platform, Microsoft. “Our collaboration with Snowflake is an example of our commitment to driving open innovation and expanding the boundaries of what AI can accomplish.”

“The continued advancement — and healthy competition between — open source AI models is pivotal not only to the success of Perplexity, but the future of democratizing generative AI for all,” said Aravind Srinivas, Co-Founder and CEO, Perplexity.We look forward to experimenting with Snowflake Arctic to customize it for our product, ultimately generating even greater value for our end users.”
“Snowflake and Reka are committed to getting AI into the hands of every user, regardless of their technical expertise, to drive business outcomes faster,” said Dani Yogatama, Co-Founder and CEO, Reka. “With the launch of Snowflake Arctic, Snowflake is furthering this vision by putting world-class truly-open large language models at users’ fingertips.”

“As an organization at the forefront of open source AI research, models, and datasets, we’re thrilled to witness the launch of Snowflake Arctic,” said Vipul Ved Prakash, Co-Founder and CEO, Together AI. “Advancements across the open source AI landscape benefit the entire ecosystem, and empower developers and researchers across the globe to deploy impactful generative AI models.”

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Artificial Intelligence

Vechain and SingularityNet Combine Blockchain + AI To Drive Sustainability and Build Advanced Enterprise-Grade Tools



Vechain and SingularityNET, industry leaders in blockchain and artificial intelligence (AI) respectively, have announced their strategic collaboration. This partnering of technical giants unites powerful emerging technologies with the potential to radically change how the global economy operates, offering powerful enterprise-grade tools to tackle challenges in the field of sustainability and traditional businesses.

In particular, the alliance holds great promise for vechain’s ambitions with Boston Consulting Group, partners, collaborating on building ‘ecosystems’ wherein individuals and businesses are incentivised to act sustainably. SingularityNet’s AI capabilities offer immense potential to enhance and improve these ecosystems, utilising AI technology to pore over data, and improve their efficacy.

Vechain and SingularityNET intend to launch joint research initiatives to fortify the efficacy of each respective platform and ingrain the pair at the heart of future digital development. The combination of these technologies can equip businesses with intelligent tools, signalling the onset of a new phase in the era of digitisation.

Dr. Ben Goertzel, the visionary CEO of SingularityNET, expressed his excitement for the massive potential of this partnership:

“The last few years have taught the world that when the right AI algorithms meet the right data on sufficient processing power, magic can happen.

What’s even better is when the algorithms, data and processing are decentralized in deployment, ownership and control — which is exactly the sort of magic that’s going to happen putting the SingularityNET ecosystem’s AI algorithms together with vechain’s deep and diverse enterprise data, on the joint, secure distributed processing power of the two networks.

This combined power will be applicable to sustainability as one of our initial focus areas, but in the end extends across essentially all vertical markets. It’s hard to overestimate the potential here.”

Vechain’s CTO Antonio Senatore commented:

“We’re excited to be collaborating with leading Web3 AI platform, SingularityNET, combining our rich streams of enterprise data with SingularityNET’s powerful and versatile platform.”

“Blockchain and AI offer game-changing capabilities for industries and enterprises and are opening new avenues of operation. We look forward to working closely with the SingularityNET team to build out new services and continue to advance the fore of possibility in web3 and sustainability.”

Vechain and SingularityNET are enabling a new, more interconnected and automated world, driving new capabilities in the fields of industry and in particular, for action around sustainability.

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Artificial Intelligence

Deepdub and OOONA Announce Strategic Partnership to Expand AI-Based Dubbing Solutions to Global Entertainment and Media Clients




Deepdub, the leading AI-based audiovisual dubbing and language localization company, today announced a partnership with OOONA, a major media localization software provider. This collaboration will bring Deepdub’s advanced dubbing solutions to OOONA’s extensive entertainment and media clients worldwide.

Through this partnership, OOONA will implement a process for connecting their clients to Deepdub’s services. This will enable media companies and content creators worldwide to instantly access Deepdub’s innovative dubbing solutions. Companies will be able to submit their content localization needs with ease via OOONA’s platform and receive tailored proposals from Deepdub that leverage the power of AI emotion-prompting technology. Going forward, clients stand to benefit from more efficient workflows and access to groundbreaking dubbing capabilities unlocking flexibility and scale.

“OOONA’s unmatched expertise in media localization, honed from providing pioneering management and production tools to the biggest names in the sector, makes them an ideal partner,” said Ofir Krakowski, CEO and co-founder of Deepdub. “This collaboration gives us the opportunity to introduce our advanced AI dubbing technology to new clients across the entertainment industry and beyond.”

OOONA is trusted by leading media localizers, broadcasters and a vast user base spanning over 170 countries. “We continue to stay true to our mission of being the core platform that integrates anything our clients need, including any opportunities AI-based solutions bring for localizing audiovisual assets,” said Wayne Garb, CEO and co-founder of OOONA. “We are thrilled to collaborate with Deepdub and further strengthen the services we provide to our customers globally.”

About Deepdub

Deepdub aims to bridge the language barrier and cultural gap of entertainment experiences for international audiences across TV, Film, Advertising, Gaming and e-learning. We provide a high-quality localization service for entertainment content using deep learning and AI algorithms. Deepdub plugs into the post-production process of content owners and provides an end-to-end solution for all of their localization needs. Deepdub’s team consists of technology entrepreneurs, engineers, and scientists, as well as dubbing and post-production specialists with extensive industry experience. The advisory board features prominent media executives such as Kevin Reilly, who held the position of Chief Content Officer at HBO Max and president of TNT, TBS, and truTV, and Emiliano Calemzuk, the former President of Fox Television Studios.

For more information about Deepdub, visit 


OOONA.Net Ltd ( is a globally recognized provider of professional management and production tools for the media localization industry. Renowned for its state-of-the-art software catering to subtitling, voiceover, dubbing and captioning needs, OOONA’s modular, pay-as-you-go pricing model empowers users to tailor solutions to their unique requirements. Trusted by leading media localizers, broadcasters and a vast user base spanning over 170 countries, OOONA continues to trailblaze advancements in the field of media localization.

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