Abstract: Example implementations are described for a secure distributed system/platform for facilitating division of a collaborative efforts between a plurality of entities into various future obligations and potential rewards and for processing such obligations and rewards into a binding forward purchase agreement. The obligation and rewards of such Forward Purchase Agreement may be sectioned, codified, and implemented as a smart contract in, for example, a distributed ledger system. In some specific applications, a secure distributed collaboration system is disclosed for investors to promote development of a new technology solution for the future using forward purchasing agreement without having to know exactly which innovators will succeed in creating and demonstrating practicability in that technology space.

Abstract: A system that transforms electronic messages into annotated messages that include contextual information to aid a recipient in utilizing the electronic message, understanding its meaning, and responding to the message. Annotations are additions or modifications to the original message with contextual information that is related to the features and contents of the original message. Message features are extracted and used to search one or more sources of contextual information. Relevant items are retrieved and added to the message, for example as attachments, hyperlinks, or inline notes. Machine learning techniques may be used to generate or refine modules for feature extraction and information selection. Feedback components may be used to track the usage and value of annotations, in order to iteratively improve the annotation system.

Abstract: A system that transforms electronic messages into annotated messages that include contextual information to aid a recipient in utilizing the electronic message, understanding its meaning, and responding to the message. Annotations are additions or modifications to the original message with contextual information that is related to the features and contents of the original message. Message features are extracted and used to search one or more sources of contextual information. Relevant items are retrieved and added to the message, for example as attachments, hyperlinks, or inline notes. Machine learning techniques may be used to generate or refine modules for feature extraction and information selection. Feedback components may be used to track the usage and value of annotations, in order to iteratively improve the annotation system.

Abstract: A system that transforms electronic messages into annotated messages that include contextual information to aid a recipient in utilizing the electronic message, understanding its meaning, and responding to the message. Annotations are additions or modifications to the original message with contextual information that is related to the features and contents of the original message. Message features are extracted and used to search one or more sources of contextual information. Relevant items are retrieved and added to the message, for example as attachments, hyperlinks, or inline notes. Machine learning techniques may be used to generate or refine modules for feature extraction and information selection. Feedback components may be used to track the usage and value of annotations, in order to iteratively improve the annotation system.

Abstract: A system that transforms electronic messages into annotated messages that include contextual information to aid a recipient in utilizing the electronic message, understanding its meaning, and responding to the message. Annotations are additions or modifications to the original message with contextual information that is related to the features and contents of the original message. Message features are extracted and used to search one or more sources of contextual information. Relevant items are retrieved and added to the message, for example as attachments, hyperlinks, or inline notes. Machine learning techniques may be used to generate or refine modules for feature extraction and information selection. Feedback components may be used to track the usage and value of annotations, in order to iteratively improve the annotation system.

Abstract: Among other things, we describe enabling two or more users to share a workspace that is dynamically populated by artifacts of electronic communications among the users that are expressed in a form of at least one of social network posts and email messages, and in which the users can interact using the artifacts in any of the forms.

Abstract: A method, system, and program product stored on a computer-readable medium, for conveying reliable identity in electronic collaboration that includes evaluating information element(s) of an electronic interaction (e.g., message) so as to obtain a “confidence value” of the identity of the sender of the electronic interaction, based on the evaluation of the information element(s) and then mapping, on a spectrum, either in a visual, aural, haptic olfactory, or a combination of modes, the “confidence value” to the electronic interaction sender. May be employed in e-mail, VoIP, instant messaging, and the like.