Farshid Alizadeh-Shabdiz
Boston, Massachusetts, United States
903 followers
500+ connections
About
A hands-on technical leader with eyes toward business needs, who enjoys a dynamic…
Activity
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mimik ai: Connecting the Dots for Hybrid Edge AI ! We’re pleased to introduce mimik ai, our universal cloud-native operating environment for hybrid…
mimik ai: Connecting the Dots for Hybrid Edge AI ! We’re pleased to introduce mimik ai, our universal cloud-native operating environment for hybrid…
Liked by Farshid Alizadeh-Shabdiz
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Dinner Discussions with my Daughter In a recent presentation to clients, I joked that topics like LRCNs and Hybrid Securities might not typically be…
Dinner Discussions with my Daughter In a recent presentation to clients, I joked that topics like LRCNs and Hybrid Securities might not typically be…
Liked by Farshid Alizadeh-Shabdiz
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I am honored to be recognized as a finalist for the 2024 Boston CIO ORBIE Award. Boston is home to so many world-class technology leaders and being…
I am honored to be recognized as a finalist for the 2024 Boston CIO ORBIE Award. Boston is home to so many world-class technology leaders and being…
Liked by Farshid Alizadeh-Shabdiz
Experience
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Education
Patents
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Calculation of quality of wlan access point characterization for use in a wlan positioning system
Issued US 7551579
Methods and systems for classifying WLAN access points according to the quality of estimation of characteristics of the WLAN access points are provided. The classifications may be used to scale a reference database and quantify an expected error of estimation of the characteristics of the access points. WLAN access points may be classified based on their impact on a user's position, speed of travel, and direction of travel estimation accuracy in a WLAN positioning system. A method for…
Methods and systems for classifying WLAN access points according to the quality of estimation of characteristics of the WLAN access points are provided. The classifications may be used to scale a reference database and quantify an expected error of estimation of the characteristics of the access points. WLAN access points may be classified based on their impact on a user's position, speed of travel, and direction of travel estimation accuracy in a WLAN positioning system. A method for determining a quality of estimation of characteristics of a Wi-Fi access point comprises a Wi-Fi enabled scanning device measuring a number of received signal strength (RSS) samples of the Wi-Fi signal transmitted by the Wi-Fi access point. A total distance traveled by the Wi-Fi enabled scanning device while measuring the number of RSS samples is estimated and used to estimate the quality of estimation of characteristics of the Wi-Fi access point.
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Methods and systems for estimating a user position in a WLAN positioning system based on user assigned access point locations
Issued US 7471954
A method of estimating a location of a WLAN-enabled user-device in a WLAN-based positioning system is provided. The WLAN-enabled device receives signals transmitted by WLAN-enabled access points in range of the WLAN-enabled user-device so that observed WLAN-enabled access points identify themselves. The method includes accessing a master database that associates WLAN-enabled access points with corresponding audited locations as determined by an audit of a relatively large geographic area and…
A method of estimating a location of a WLAN-enabled user-device in a WLAN-based positioning system is provided. The WLAN-enabled device receives signals transmitted by WLAN-enabled access points in range of the WLAN-enabled user-device so that observed WLAN-enabled access points identify themselves. The method includes accessing a master database that associates WLAN-enabled access points with corresponding audited locations as determined by an audit of a relatively large geographic area and obtaining location information for any identified WLAN-enabled access point. The method includes accessing a supplemental database to obtain inferred location information corresponding to any identified WLAN-enabled access point. The supplemental database has a relatively small set of WLAN-enabled access points and corresponding inferred locations. The inferred locations are inferred based on input by a user of the WLAN-based positioning system. The method includes estimating a location of the WLAN-enabled user-device based on the audited location information and the inferred location information.
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Systems for and Methods of Determining Likelihood of Relocation of Reference Points in a Positioning System
Filed US 2011/0306359
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Systems for and Methods of Determining Likelihood of Reference Point Identity Duplication in a Positioning System
Filed US 2011/0306358
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Systems for and Methods of Determining Likelihood of Atypical Transmission Characteristics of Reference Points in a Positioning System
Filed US 2011/0306357
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Systems for and Methods of Determining Likelihood of Mobility of Reference Points in a Positioning System
Filed US 2011/0306360
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Methods of and Systems for Measuring Beacon Stability of Wireless Access Points
Filed US 2011/0306361 A1
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Method and System for Estimating Range of Mobile Device to Wireless Installation
Filed US 2011/0045840
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A method for estimating position using WLAN access point radio propagation characteristics in a WLAN location based service is provided.
US US Patent 20196621
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A method of and system for estimating the range of a mobile device to a wireless installation is disclosed.
US US Patent US2013217390
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A method of and system for estimating the range of a mobile device to a wireless installation is disclosed.
US US Patent US2013217390
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CERTIFIED LOCATION FOR MOBILE DEVICES
US 20150241548
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Determining A Dilution of Precision Metric Using Two or Three GPS Satellites
US US20110080318 A1
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ESTIMATING DEMOGRAPHICS ASSOCIATED WITH A SELECTED GEOGRAPHIC AREA
US 20150245175
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Improvement of the accuracy and performance of the hybrid positioning system
US WO2011041298 A1
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Method and system for selecting and providing a relevant subset of Wi-Fi location information to a mobile client device so the client device may estimate its position with efficient utilization of resources
US US Patent 8983493
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Method for estimating the speed and bearing of a Wi-Fi enabled device using WLAN radio signals in a WLAN based location service
US US Patent 9008690
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Method of and Systems for Privacy Preserving Mobile Demographic Measurement of Individuals, Groups and Locations Over Time and Space
US 13/901,822
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Method of determining device location using the stored locations for the identified Wi-Fi access points, the signal strengths of the received messages and the chosen location-determination algorithm
US US Patent 8965412
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Method of estimating an expected error of a position estimate for use in a WLAN positioning system that estimates the position of a WLAN-enabled device
US US Patent 8909245
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Method of estimating demographic information associated with a selected tile based on tracks of a plurality of mobile device users
US US Patent 9031580
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Methods and systems of continuously optimizing data in Wi-Fi positioning systems
US US Patent 9037162
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Methods and systems of hybrid positioning for increasing the reliability and accuracy of location estimation
US US Patent 8890746
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Methods of and systems for measuring beacon stability of wireless access points are provided
US US Patent 8971923
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Methods of and systems for resolving multiple location estimate conflicts in a WLAN-positioning system.
US US Patent US2011235532
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System and method of gathering WLAN packet samples to improve position estimates of WLAN devices.
US US Patent US9103900
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Systems and methods for using a satellite positioning system to detect moved WLAN access points
US US Patent 9013350
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Systems for and methods of determining likelihood of atypical transmission characteristics of reference points in a positioning system
US US Patent 9014715
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Systems for and methods of determining likelihood of mobility of reference points in a positioning system are disclosed
US US Patent 8971915
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Systems for and methods of determining likelihood of reference point identity duplication in a positioning system
US US Patent 8996032
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Systems for and methods of determining likelihood of relocation of reference points in a positioning system are disclosed
US US Patent 8983504
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Technique for using cached information with a WLAN positioning system to obtain an estimate of a position of a mobile device.
US US Patent US2013241776
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Techniques for estimating a position of a user device using optimized scanning
US 10317507
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Techniques for estimating demographic information
US 10304086
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method and system for increasing the accuracy of a WLAN based position estimate using cellular positioning information
US US Patent 9001743
Honors & Awards
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MIT Sloan Leadership Fellowships Award
MIT
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MIT Sloan Leadership Fellowships Award
MIT
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Shantha Mohan Ph.D.
"Ott's Product Management class at CMU-SV is structured to give students a holistic understanding of the product lifecycle. The course emphasizes a balanced approach, ensuring that students not only grasp the theoretical aspects of product management but also gain practical experience. By working on real projects, students are taken through each phase of the product lifecycle, fostering a deep and comprehensive understanding." This excellent article by Utkarsh Khandelwal and Philip Geist gives you a peek at what it is like to take the Product Management course by Adrian C. O. at Carnegie Mellon University - Integrated Innovation Institute. https://lnkd.in/gHDpc8gR
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Eric Bonabeau
I should add to my earlier post about Colin F.'s blog on #LLM and #genAI hallucinations that (the always interesting) Andrej Karpathy is enthusiastically embracing the idea of hallucinations being a feature, not a bug, according to this X-tweet: https://lnkd.in/gRgvG2gW I can't agree more. The issue is, to borrow Colin F.'s vernacular, that genAI is like a hammer and people see nails everywhere: there may a few actual nails out there, in the space of dreams and creativity, but most nail-looking use cases are not nails at all. -- @karpathy # On the "hallucination problem" I always struggle a bit with I'm asked about the "hallucination problem" in LLMs. Because, in some sense, hallucination is all LLMs do. They are dream machines. We direct their dreams with prompts. The prompts start the dream, and based on the LLM's hazy recollection of its training documents, most of the time the result goes someplace useful. It's only when the dreams go into deemed factually incorrect territory that we label it a "hallucination". It looks like a bug, but it's just the LLM doing what it always does. At the other end of the extreme consider a search engine. It takes the prompt and just returns one of the most similar "training documents" it has in its database, verbatim. You could say that this search engine has a "creativity problem" - it will never respond with something new. An LLM is 100% dreaming and has the hallucination problem. A search engine is 0% dreaming and has the creativity problem. All that said, I realize that what people *actually* mean is they don't want an LLM Assistant (a product like ChatGPT etc.) to hallucinate. An LLM Assistant is a lot more complex system than just the LLM itself, even if one is at the heart of it. There are many ways to mitigate hallcuinations in these systems - using Retrieval Augmented Generation (RAG) to more strongly anchor the dreams in real data through in-context learning is maybe the most common one. Disagreements between multiple samples, reflection, verification chains. Decoding uncertainty from activations. Tool use. All an active and very interesting areas of research. TLDR I know I'm being super pedantic but the LLM has no "hallucination problem". Hallucination is not a bug, it is LLM's greatest feature. The LLM Assistant has a hallucination problem, and we should fix it. </rant> Okay I feel much better now :)
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