AWS's Shahid Mohammed and Darktrace's Michael Beck discuss how generative AI innovations are transforming cybersecurity by both enhancing defences and introducing new, sophisticated threat management strategies.

Topics Include:

• Shahid Mohammed introduces himself as a lead solution architect at AWS.
• Mike Beck is Global Chief Information Security Officer at Darktrace.
• Darktrace specializes in AI-driven cybersecurity solutions for digital environments.
• Darktrace secures multiple digital data pots: email, network, cloud, SaaS, and endpoint.
• The conversation focuses on innovation in cybersecurity through AI.
• Mike emphasizes the benefits of Gen AI despite its security risks.
• Gen AI enables more complex, targeted attacks against organizations.
• Attackers use Gen AI to tailor attacks through phishing and deepfakes.
• Gen AI increases phishing complexity by eliminating common detection cues.
• Data privacy risks arise when large models process sensitive business data.
• Businesses must be mindful of AI’s impact on data sovereignty and security.
• Shahid compares the cybersecurity space to an arms race due to Gen AI.
• Mike stresses the importance of choosing the right AI for each task.
• Darktrace uses unsupervised machine learning and Gen AI together for defense.
• AI is essential for scaling cybersecurity efforts given today's threat complexity.
• Darktrace relies on AWS cloud for compute power, scaling, and innovation.
• AWS infrastructure helps accelerate Darktrace's R&D and operations securely.
• Security leaders should implement Gen AI policies and training.
• Mike advises technical controls and monitoring for safe Gen AI use.
• Gen AI is here to stay, but businesses must handle its security implications carefully.

Participants:

• Michael Beck – Global CISO - Darktrace
• Shahid Mohammed – Solution Architect Manager – Amazon Web Services

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

Daryl Martis of Salesforce and Rashna Chadha of AWS share how Amazon Bedrock integrates with Salesforce to enhance AI applications, highlighting the partnership's strategic benefits, AI model customization, and secure deployment options.

Topics Include:

• Introduction to Amazon Bedrock and Salesforce partnership.
• Overview of Amazon Bedrock as an API-based generative AI service.
• The strategic collaboration between AWS and Salesforce.
• Salesforce Data Cloud and its integration with Amazon Bedrock.
• Overview of Salesforce Einstein and its use of Amazon SageMaker.
• Recent AI launches between Salesforce and AWS, including Slack AI and MuleSoft.
• Use cases of AI services like Amazon Textract within Salesforce.
• Bringing Your Own Large Language Model (BYO LLM) with Bedrock.
• Foundation models offered by Amazon Bedrock (Anthropic, Cohere, Llama).
• Overview of security, privacy, and compliance in Bedrock AI services.
• Salesforce Data Cloud’s unified customer data and real-time AI capabilities.
• Bedrock’s support for custom AI model evaluation and metrics.
• Consumption models in Bedrock: on-demand vs. provision throughput.
• Bedrock’s agent capabilities for real-world applications like scheduling.
• Demo of using Amazon Bedrock models within Salesforce.

Participants:

• Daryl Martis – Director of Product Management, Einstein AI - Salesforce
• Rashna Chadha – AI/ML Specialist – Principal Solution Architect – Amazon Web Services

See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon/isv/

Ashish Arora, Head of Engineering & Machine Learning, Product Analytics at Autodesk, shares how personalized AI-powered experiences and real-time data can drive product adoption, featuring insights into Autodesk’s transformation journey, leveraging machine learning, and delivering actionable recommendations to millions of users.

Topics Include:

• Real-time data description and examples
• Leveraging AWS for real time and generative AI services
• Autodesk’s journey leveraging AWS to transform architecture and deliver personalized insights
• Overview of Autodesk and product portfolio
• Utilizing data gathered for customers
• Personalized data-driven insights for customers on Autocad and other products
• Descriptive insights: providing usage data for customers
• Prescriptive insights: Making recommendations to customers based on their workflows
• Predictive insights: Using ML to recommend products and features
• Autodesk processes 100+ billion events across all products, delivered 350+ million insights to customers, served to 3.5 million customers
• Example walkthrough – Rachael
• Architecture of Autodesk data and insight process
• Leveraging LLMs – Sagemaker and Bedrock
• Bringing it altogether
• Session wrap up

Participants:

• Ashish Arora – Head of Engineering & ML, Product Analytics - Autodesk
• Brian Slater – Principal Solutions Architect – Amazon Web Services