Curated for content, computing, and digital experience professionals

Category: Computing & data (Page 6 of 87)

Computing and data is a broad category. Our coverage of computing is largely limited to software, and we are mostly focused on unstructured data, semi-structured data, or mixed data that includes structured data.

Topics include computing platforms, analytics, data science, data modeling, database technologies, machine learning / AI, Internet of Things (IoT), blockchain, augmented reality, bots, programming languages, natural language processing applications such as machine translation, and knowledge graphs.

Related categories: Semantic technologies, Web technologies & information standards, and Internet and platforms.

Salesforce launches Agentforce

Salesforce, a CRM (customer relationship management) provider, announced the general availability of Agentforce, a new layer on the Salesforce Platform that enables companies to build and deploy AI agents that can autonomously take action across business functions. Agentforce uses reasoning abilities to make decisions and take action, like resolving customer cases, qualifying sales leads, and optimizing marketing campaigns. Agentforce doesn’t depend on human engagement to get work done; these agents can be triggered by changes in data, business rules, pre-built automations, or signals via API calls from other systems.

Agentforce includes out-of-the-box agents that are easy to customize and deploy with low-code or no-code tools and that work around the clock across any channel. Users can customize pre-built agents to serve any industry and use case, like retail with order management topics, or financial services with billing and payment support topics.

With Agentforce, there’s no need to DIY (do it yourself) your AI. Customers can instantly turn their existing Flows, prompt templates, Apex, and APIs into agent actions, connecting to enterprise data, security models, and automations‌ with tools like Data Cloud, Slack, and MuleSoft. Salesforce admins and developers can use natural language to create instructions for agents.

https://www.salesforce.com/news/press-releases/2024/10/29/agentforce-general-availability-announcement/

Semantic Web Company and Ontotext merge to create Graphwise

Semantic Web Company and Ontotext today announced the two companies have merged to become Graph AI provider, Graphwise. Semantic Web Company brings expertise in knowledge engineering, semantic AI and intelligent document processing, while Ontotext brings a versatile graph database engine and AI models for linking and unifying information.

Combining Ontotext GraphDB’s data management capabilities with PoolParty, knowledge and content management offerings from Semantic Web Company, Graphwise has created a comprehensive knowledge graph management platform, which includes complete multi-modal data support – unstructured, semi-structured and structured data. The Graphwise Platform, will enable customers to benefit from: 

  • Sophisticated, accurate and reliable AI applications that leverage the power of knowledge graphs for applications like Graph RAG, NLP, recommendation systems, and predictive analysis. 
  • Support unstructured and semi-structured data management into data fabric processes. 
  • The ability to scale effortlessly, while ensuring data remains well-structured and classified. This enables businesses to build AI systems capable of navigating vast networks of interconnected information without sacrificing accuracy or performance. 
  • Enhanced flexibility in designing models by providing the tools necessary in one platform to simplify architectural decisions.
  • A combined partner ecosystem and a broader market which creates more opportunities, including significantly larger project volumes. 

https://graphwise.ai

Perplexity introduces Internal Knowledge Search and Spaces

From industry professionals to hobbyists, people use Perplexity in ways we never imagined, but we want to give users even more flexibility and control over the types of sources they prompt, which is why we’re excited to introduce Internal Knowledge Search and Spaces.

While file upload has been part of Perplexity for some time, one of our most requested features has been the ability to search internal files alongside the web. With Perplexity Pro and Enterprise Pro, you can now search across both public web content and your own internal knowledge bases. Seamlessly access and synthesize the best information from all sources to get the answers you need, faster.

We’ve also reinvented how teams research and organize information with Perplexity Spaces — AI-powered collaboration hubs that can be customized to your specific use case. You can invite collaborators, connect internal files, and customize the AI assistant by choosing your preferred AI model and setting instructions for how it should respond.

Spaces gives you access controls over who can access your research and files. For Enterprise Pro customers files and searches are excluded from AI training by default. Pro users can choose to opt out of AI training in their settings.

https://www.perplexity.ai/enterprise

Sitecore launches Sitecore Stream

Sitecore, a digital experience software provider, today announced Sitecore Stream to address challenges and opportunities faced by enterprise marketing teams. Built on Microsoft Azure OpenAI Service, Sitecore Stream helps orchestrate a seamless marketer experience across Sitecore solutions, including XM Cloud, Content Hub, and Experience Platform (XP).

Sitecore Stream leverages generative AI to simplify marketing workflows and enhance productivity through orchestration, content intelligence, and automated assistance. Sitecore Stream leverages Sitecore’s composable product architecture, enabling full interoperability across a brand’s existing martech stack, with built-in AI guardrails to help preserve brand compliance and data privacy. Sitecore Stream includes:

  • Brand-aware AI: Helps align marketers’ actions, recommendations, and experiences with the organization’s brand identity, values, and guidelines.
  • AI-enhanced workflows: Automates repetitive tasks to accelerate execution and boost collaboration. These workflows may be creating content, building a website page, or A/B testing a call to action to help marketers stay in a productive flow.
  • Generative copilots: For brand, brief, content, and experience creation and optimization, these help marketers stay true to their brand and brief as they complete their work.

Sitecore Stream capabilities are available today.

https://www.sitecore.com/products/sitecore-stream

MongoDB releases MongoDB 8.0

MongoDB, Inc. released MongoDB 8.0, providing performance improvements, reduced scaling costs, and additional scalability, resilience, and data security capabilities. MongoDB 8.0 is available on AWS, Google Cloud, and Microsoft Azure through MongoDB Atlas, on MongoDB Enterprise Advanced for on-premises and hybrid deployments, and as a free download with MongoDB Community Edition. Capabilities: 

  • Optimized performance for a wide variety of applications. 
    Architectural optimizations reduced memory usage and query times, has more efficient batch processing capabilities, and handles higher volumes of time series data.
  • Encryption that unlocks new use cases.
  • Queryable Encryption allows customers to encrypt sensitive application data, store it securely and run expressive queries on the encrypted data for processing.
  • Faster horizontal scaling for high availability.
  • Sharding improvements in MongoDB 8.0 distribute data across shards faster without the need for additional configuration. 
  • Resilience for unexpected application demand. 
  • The ability to set a default maximum time limit for running queries, to reject recurring types of problematic queries, and to set query settings to persist through events like database restarts. 
  • Reduced costs and increased scale for vector applications.
  • With vector quantization, customers can build a wide range of search and AI applications at higher scale and lower cost.

https://www.mongodb.com/products/updates/version-release

Movable Ink adds Da Vinci to Adobe Experience Cloud integrations

Movable Ink announced the integration of Movable Ink Da Vinci and Adobe Journey Optimizer. This adds to existing Movable Ink built integrations into Adobe Experience Cloud applications, including Adobe Target, Adobe Commerce, Adobe Real-Time CDP, and Adobe Campaign.

The new integration of Movable Ink Da Vinci, an AI-powered content personalization solution, and Adobe Journey Optimizer accelerates the creation of custom marketing content for high-volume campaigns. When orchestrating customer journeys in Adobe Journey Optimizer, joint customers can leverage their enterprise-specific data and campaign assets to inform the intelligent assembly and personalization of email templates and content variations unique to each subscriber. Customers can then bring those assets into Adobe Journey Optimizer to further personalize, optimize, and deploy their email marketing campaigns. This builds on existing integrations between Movable Ink Da Vinci and Adobe Campaign, which aims to maximize customer engagement for large-scale campaigns and reach dormant subscribers.

Movable Ink has also built existing integrations between Adobe and Movable Ink Studio – an open-time, in-the-moment content-generation solution. In Movable Ink Studio, brands can leverage insights from applications like Adobe Real-Time CDP, Commerce, and Target to generate personalized content for email and mobile messages.

https://movableink.com/adobe-and-movable-ink

Optimizely to acquire NetSpring

Optimizely, a digital experience platform (DXP) provider and experimentation platform, announced it has signed a definitive agreement to acquire the warehouse native analytics platform NetSpring. With this acquisition, Optimizely’s DXP will provide “warehouse native” analytics, enabling customers to tie experimentation and other digital experience activities to business metrics and outcomes that resides in customers’ data warehouses. Experimentation teams can also apply Optimizely’s Stats Engine and advanced analysis to data inside a customer’s data warehouse to gain access to visualization capabilities. Based on the technology that NetSpring provides, all of this can happen without extracting data out of cloud data warehouses such as Snowflake, Databricks, Google BigQuery or Amazon Redshift, which maximizes speed, minimizes cost and protects customer data privacy. The new capabilities will also serve as the future analytics platform across all of Optimizely One, an operating system for marketers.

Founded in 2019 by the same team as Business Intelligence (BI) company ThoughtSpot, NetSpring is an advanced platform in the warehouse native analytics space. With a proven product and large enterprise deployments, NetSpring will quickly complement Optimizely’s offerings, starting with experimentation. The transaction, which is expected to be completed in the fourth quarter of 2024, is subject to customary closing conditions.

https://www.optimizely.com/netspring

Ai2 launches family of open multimodal models

The Allen Institute for AI (Ai2) announced the launch of Molmo, a family of state-of-the-art multimodal models. This family includes our best Molmo model, closing the gap between close and open models, an open, efficient, and powerful multimodal model. Currently, most advanced multimodal models can perceive the world and communicate with us, Molmo goes beyond that to enable one to act in their worlds, unlocking a new generation of capabilities, from sophisticated web agents to robotics:

  • Exceptional image understanding: Molmo can accurately understand a wide range of visual data, from everyday objects and signs to complex charts, messy whiteboards, clocks, and menus.
  • Actionable insights: To bridge the gap between perception and action, Molmo models can point to what they perceive, empowering capabilities that require spatial knowledge. Molmo can point to UI elements on the screen, enabling developers to build web agents or robots that can navigate complex interactions on screen and within the real-world.

Molmo was designed and built in the open and Ai2 will be releasing all model weights, captioning and fine-tuning data, and source code. Select model weights, inference code, and demo are available, providing open access to enable continued research and innovation in the AI community.

https://molmo.allenai.org/blog

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