Nathan Beach’s Post

#AI is not a one-size-fits-all endeavor. Your journey accelerates when you have a thoughtful and intentional strategy. Learn how Oracle can be your partner in driving a proven model of executing an #AI strategy for your organization.

Cohere is on a roll! Its latest model, Command R+, has beaten GPT-4 on the Arena leaderboard and is now available on HuggingChat. Unlike OpenAI, Cohere focuses on enterprises rather than catering to consumers with conversational chatbots. “We do not have and never will have a cash-burning consumer chatbot,” said Martin Kon , the COO of Cohere. Cohere offers several models in three categories: Embed, Command, and Rerank. Each category serves specific use cases and can be tailored to suit particular needs. Cohere’s latest model, Command R+, will soon be available on Oracle Cloud Infrastructure (OCI) and Microsoft Azure , alongside Amazon Sagemaker. Aidan Gomez

The new family of models follows the trend of moving from huge all-in-one, jack-of-all-trades constructs to more specialized models designed to more nimbly handle specific tasks. https://lnkd.in/gcm4u2jS #AWSReInvent #reInvent #AWS #Cloud

The article highlights the importance of choosing the right cloud and AI services for businesses and balancing cost-effectiveness with functionality.

Are you up to speed on #genai in your #cloud #stack? A recent report from cloudcomputing-news.net reveals that #azurecloud is leading the way with their #azureai and #azureaistudio, surpassing #awsbedrock. Check out the article to learn more about how generative AI is becoming commonplace in cloud business models. #AI #cloudcomputing #technews Link: https://lnkd.in/eeWjiYTF

Many of the 20 #cloud #AI companies on this list are leading the market in terms of #LLMs and #FMs, which are the core of #GenAI capabilities.

AI fuels cloud race among Microsoft, AWS, & Google The rapid evolution of artificial intelligence (AI) has ignited a competitive race among major cloud service providers, particularly Microsoft, Amazon Web Services (AWS), and Google. Recent data from the Global Cloud Projects Report and Da... https://lnkd.in/dtqrJA_U #CLOUDCOMPUTING_DIGITALTRANSFORMATION_AI_ECOMMERCE_TECHINNOVATION

Wiz's recent report, "State of AI in the Cloud 2024", reveals the astonishing speed at which artificial intelligence (AI) is being adopted in cloud environments. As a cybersecurity and AI expert, I find several key insights from this report to be particularly noteworthy for organizations leveraging cloud-based AI services. First and foremost, the adoption of managed AI services has reached an unprecedented level, with over 70% of cloud environments now employing these services. This widespread adoption is nearly on par with managed Kubernetes services, despite AI services being much newer. Microsoft's Azure AI Services, including Azure OpenAI, lead the pack among major cloud service providers. The explosive growth of Azure OpenAI is especially striking. Over a mere 4-month period in 2023, the number of Azure OpenAI instances more than tripled across cloud environments, far outpacing the growth of other Azure AI services. This suggests that organizations are eagerly embracing the capabilities of generative AI models like GPT. However, while AI adoption is undoubtedly high, the report indicates that many organizations may still be in an experimental phase. Around 32% have deployed fewer than 10 instances of managed AI services, hinting that they are cautiously testing the waters before fully committing resources. From a security standpoint, the rapid uptake of AI in the cloud echoes the early days of cloud computing itself—widespread adoption is occurring without fully established standards and governance. As with any swiftly adopted technology, potential security drawbacks are beginning to emerge, such as Microsoft's accidental exposure of 38 terabytes of AI data. Looking ahead, I believe that the cost and security of AI model training and inference will become critical priorities for organizations. Monitoring and optimizing the expenses associated with developing and operating AI models, both for internal use and customer-facing applications, will be key. Equally important will be implementing robust security controls and observability to manage the new attack surface introduced by AI. To navigate this AI-driven landscape securely, I recommend the following strategies: 1. Invest in an AI-SPM (Security Posture Management) solution to gain visibility into your organization's AI service usage and eliminate blind spots that could lead to "Shadow AI." 2. Follow best practices for securely building multi-tenant services that incorporate generative AI models, ensuring the safety of your customers' data. 3. Foster a culture of shared security ownership around AI across your organization. Security teams must collaborate closely with developers, cloud engineers, data scientists, and AI practitioners to proactively address risks.

The rapid adoption of AI in the cloud has reached unprecedented levels, with over 70% of cloud environments now employing managed AI services, nearly on par with managed Kubernetes. However, this swift uptake has outpaced the establishment of robust security standards and governance, leading to potential vulnerabilities and risks. To navigate this AI-driven landscape securely, organizations must prioritize visibility, implement best practices for secure multi-tenant services, and foster a culture of shared security ownership across teams. You can read the detailed analysis in the post 👇

If you're looking to stay ahead of the curve, here are the top 20 cloud AI companies to watch out for in 2024. From AWS and Microsoft Azure to Altair, MongoDB and Dynatrace. #CloudComputing #ArtificialIntelligence #AIcompanies