our News

December 6, 2023

Generative AI Hallucinations

Problem in GenAI

Sometimes Generative AI perceives patterns that are imperceptible to people leading to an inaccurate output. We are talking about GenAI hallucinations, just like humans seeing patterns in clouds in the sky.

Hallucinations are misinterpretations due to several factors including  over-fitting, bias or inaccuracy of the training data, as well as the complexity of the large language model (LLM) used.

Causes of hallucinations

Our AI team is working on reducing the occurrence of hallucinations by optimizing data pre-processing and refining model architectures.We know that Generative pre-trained transformer (GPT) still has limitations and many researchers are working to reduce hallucinations by addressing the causes including:

  • Social biases in the training data,
  • Conflicting indications,
  • Insufficient training data: model is not trained with a diverse and representative dataset, it may lack exposure to diverse scenarios and contexts,
  • Model complexity, complex models can produce unexpected results.
  • Over-fitting, model is tuned too tight,
  • Ambiguity in the training data, training data contains contradictory or ambiguous content,
  • Data Anomalies and Outliers, training data can impact the model behavior,
  • Model complexity: Very complex artificial intelligence models can sometimes produce unexpected results.
  • Non-Contextual Verification,LLMs do not possess the ability to verify information against external sources or access real-time data. 

European Ethical AI

The problems GenAI hallucinations cause are generating disinformation, providing ethical issues, and giving misleading content.

It is crucial to improve the quality of the data and algorithms and invest in research and development to make GenAI ethically sound and safe to use.

Semlab is working in close collaboration with other researchers and developers within the European industry and academia. Semlab joined R&D efforts to mitigate hallucination and maximize LLM societal benefits while minimizing bias and misleading content and working on an European Ethical AI. 

 

November 17, 2022

Innovatieproject voor geestelijke gezondheid:

Ontwikkeling van een AI-ecosysteem dat de diagnose en zorg voor psychische aandoeningen verbetert.

Met 24 partners in 5 landen introduceert Semlab als Nederlands landencoördinator dit innovatieproject, gefinancierd voor Rijksdienst voor Ondernemend Nederland in het kader van ITEA 4 (Europees cluster voor software innovatie).

Projectpartners Amsterdam Universitair Medisch Centrum, Philips NV, Technische Universiteit Eindhoven, Knowl, 5m, GGZ Oost Brabant en Semlab hebben de handen ineengeslagen om met Artificiële Intelligentie (AI) ondersteunende toepassingen te gaan ontwikkelen.

“Het Nederlandse deel is € 5,6 Miljoen”, zegt Bram Stalknecht, mede-oprichter van Semlab, “samen met deze projectpartners kunnen we AI-ondersteuning geven aan professionals in GGZ en haar cliënten.”

Wereldwijd lijden meer dan 280 miljoen mensen aan psychische aandoeningen, zoals depressie, obesitas en eetstoornissen, en dit neemt alleen maar toe met name onder jong volwassenen.

Eetstoornis is, net als depressie, moeilijk te behandelen; slechts ongeveer 50% herstelt na behandeling en zelfs na succesvolle behandeling is de terugval groot.

DAIsy zal nieuwe AI-ondersteunde oplossingen ontwikkelen voor verbeteringen op het gebied van de diagnose, selectie van de behandeling, monitoring van voeding en activiteiten, en beoordeling van de respons op de behandeling.

De Nederlandse use case richt zich op twee belangrijke psychische aandoeningen en hun wisselwerking: depressieve stoornis en eetstoornis. Voor beide ziekten zal DAIsy op AI gebaseerde tooling ontwikkelen, onderzoeken en valideren door de analyse van een breed scala van gegevensbronnen.

Het overkoepelende doel van DAIsy is om de efficiëntie, nauwkeurigheid en prognostische waarde van de behandeling van patiënten met een psychische aandoening te verbeteren.

Binnen het project zal AI worden getraind door data en expertise van Oost Brabant GGZ en Amsterdam UMC.  De ambitie is om de resultaten te delen met zorgprofessionals en een applicatie aan te kunnen bieden.
Voor meer informatie: https://itea4.org/project/daisy.html

 

January 27, 2022

AI-gedreven Uitspraakvoorspeller App ondersteund door Rijksdienst voor Ondernemend Nederland

Toegankelijke rechtspraak is een groot goed in Nederland, tegelijkertijd lopen de kosten van rechtsbijstand hoog op en zal er meer en meer beroep worden gedaan op het rechtsysteem.
Met AI kan met in een voorfase een algemene rechterlijke toets plaatsvinden waarbij relevante ‘events’ automatisch worden vergeleken met jurisprudentie dmv een artificiële intelligentie omgeving. Hiermee wordt de uitspraak voorspelt door honderdduizenden openbare zaken in onder andere rechtspraak.nl binnen een paar seconden te vergelijken met het conflict.

De applicatie zal worden gebruikt onder de beoogde afnemende organisatie MvJ&V en zal gratis toegankelijk zijn voor de burgers. Het product is intrinsiek schaalbaar en met weinig aanpassingen toepasbaar in andere rechtsgebieden, voornamelijk commerciële advocatuur en andere rechtsbijstand organisaties.

De AI zal met de nieuwe autoregressie language model van GOOGLE worden opgezet waarbij miljoenen parameters een on the fly reasoning mogelijkheid bieden om voor alle nuances in zaken toe te voegen en zo tot een juiste toetsing en oordeel te komen.

 

June 23, 2021

Semlab AI DevOps latest investment: Powerhouse Beyond State of the Art AI: Autoregressive Modeling and DeepLearning GPU Rendering Workstation

SEMLAB invests in beyond state of the art AI Development:
For our pre-training on an extremely large corpora of data and fine tuning on specific tasks SEMLAB DevOps is modelling with Autoregressive Language Models, allowing to parse over 175 billion parameters.
We improve on the fly reasoning and domain adaptation on our artificial intelligence highly autonomous systems that outperform state of the art artificial intelligence solutions at most economically valuable work.

For our Machine Learning implementation in Java agile software processes, data-driven development, reliability, and responsible experimentation we improved our
Storage frameworks including Hadoop, S3, Snowflake, Spark, Flink, Cassandra, Dynamoand Kafka and Machine Learning frameworksTensorflow, Caffe and PyTorch.
In order to process big data sets the latest NVIDIA RTX Deep learning GPU Rendering workstations will be deployed.

 

March 17, 2020

CoronaTriage wordt nu volop gebruikt

Vorige week hebben onze applicatie engineers het corona protocol van het RIVM in de Meditra triagesoftware geprogrammeerd. We zijn nu een week verder en vele eerste- en tweedelijns zorgmedewerkers gebruiken de gratis beschikbaar gestelde triagetool. We zullen deze service blijven aanbieden zolang hier behoefte aan is. Elke verandering die het RIVM maakt zullen we zo snel mogelijk verwerken zodat de gebruiker altijd de laatste inzichten heeft.

Coronatriage kunt u vinden op het volgende adres: https://coronatriage.semlab.nl/

Voor de reguliere NTS  triagesoftware ga naar: https://meditra.semlab.nl/

 

 

 

September 30, 2019

Artificial Intelligence Software Vendor SemLab partners with Reynen Court to offer its AI-enabled automated legal review, reporting, and anonymizing services via the Reynen Court marketplace and services automation platform

One single secure AI-enabled platform makes it easy and affordable to test and adopt the latest AI legal applications without the hassle of privacy, security, and proof of concepts. For Due Diligence, Legal Contract Review, GDPR compliance Semlab offers automated solutions for multi-language use. “We are very excited to be working with Reynen Court to integrate our AI legal solutions with their robust marketplace and services automation platform,” explained Bram Stalknecht, CEO SemLab, an Amsterdam-based legal technology software company.

“We are very pleased to be partnering with SemLab to make their product suite of AI-enabled automated review and anonymizing applications in multilingual domains available through our platform,” Andy Klein, Founder and CEO of Reynen Court noted. ”With Reynen Court, Legal firms and in-house counsel can test and deploy innovative solutions like those from SemLab, while saving resources on sourcing technology and setting up application security, contractual provisions, and innovation risk”.

About Reynen Court

Reynen Court LLC (www.reynencourt.com) enables law firms and corporate legal departments to speed their adoption of AI and other new technologies.  Our platform combines a solution store for legal technology with a powerful control panel that makes it easy to adopt and manage modern cloud-based software applications without having to trust firm or client content to the rapidly growing universe of vertically integrated SaaS providers.  The platform also lets firms manage subscriptions and provisioning from one place and provides valuable telemetry and enhanced interoperability between and among third-party applications.  Founded by serial Internet entrepreneur and former Cravath, Swaine and Moore associate Andrew D. Klein, Reynen Court is supported by a broad consortium of nineteen of the largest global law firms.  Clifford Chance and Latham & Watkins serve as co-chairs of the Reynen Court consortium and are also investors in the company. Paul Weiss serves as vice-chair of the consortium.

 

About Semlab

SemLab is an Artificial Intelligence Software company based in Amsterdam, The Netherlands offering Machine Learning, Natural Language Processing and Data Extraction. Semlab Anonymization is AI-driven software for removing sensitive personal data from documents.  Semlab DocReview is legal document review system that automatically creates comprehensive reports of the most common legal issues.

More at www.semlab.nl

 

January 22, 2019

SemLab €4 Million AI-driven research project open for participation to improve quality of life after cancer treatment with health & wearables data.

SemLab € 4 Million Research project  ”Artificial Intelligence for monitoring health status  combining big data from new sources of health data including mobile health apps & wearables, social-, nutrition- and health records data”. The project is now open for participants within oncology or data driven organizations.

Challenge: AI (Artificial Intelligence) can provide new opportunities to define statistical and clinical significance, but present also challenges as it requires specific analytical approaches.  Cancer treatment Information will not only be collected from traditional sources (cohorts, comprehensive electronic health records and clinical registries) but there is a fast growing number new sources which will be useful to include. Semlab indicated emerging sources from personalized mobile health apps and wearables and sources from other areas such us nutrition, social, environmental data. After informed consent this data from disparate sources effectively monitor health status of individual patients, provide overall actionable insights at the point of care and improve quality of life after the cancer treatment.

Outcome: The project outcome determining and monitoring the combined effects of cancer treatment, environment, lifestyle and genetics on the quality of life, enabling early identification of effects that can cause development of new medical conditions and/or impair the quality of life.

Bram Stalknecht: We focus on how to better acquire, manage, share, model, process and exploit big data using, AI to effectively monitor health status of individual patients, provide overall actionable insights at the point of care and improve quality of life after the cancer treatment.

Participation: Semlab already have good quality partners, but we are open to discuss participation from Oncology Hospitals, Post-oncology Organizations, Pharmaceutical Companies and Health app & wearables Manufacturers. Other companies with relevant data (social, environmental, etc.) are also welcome to discuss participation.
This is a € 4 Million EC-funding Research and Innovation project proposal.

Contact: For more info please contact our sales dept: sales@semlab.nl

 

October 8, 2018

State Secretary Mona Keijzer awarded SemLab, 2.5€ Million European Innovation project

State Secretary Mona Keijzer awarded SemLab for €2,5 Million European Innovation Project.

Eurostars Awards Eurostars Awards

Eurostars, a co-funded European Union programme,  enabled SemLab to collaborate with data analytics companies across Europe. This ranged from Big Data Analytics in Sweden, Statistic Machine Translation in Latvia to Data Integration in Turkey.  SemLab integrates high valuable tools within its Artificial Intelligence software to provide innovative solutions to its customers.

 

 

September 19, 2018

Semlab introduction video

We have recently added a new introduction video to our website. Check it out and if oyu have any questions, please let us know.


SemLab is an Artificial Intelligence Software company. We make decision support applications, of which the software is based on language technology, for especially Fintech, Legaltech and Healthcare.

 

November 15, 2017

Crypto Data: First Blockchain project for Reference Data.

blockchain2

SemLab is currently entering a Shared Reference Data project with distributed ledger technology, in order to simplify reference data processes. Reference data is a headache for financial instrument services, where there is a lack of coordination, legacy data systems and inefficient processes. SemLab will make the current legacy obsolete and stop the need of having own record keeping with inevitable and costly inconsistencies that need to be reconciled. The project aim is to tackle these problems through the distributed ledger prototype simulate the collaborative management of reference data, as well as the use of that data for corporate bond issuance. The project is now open for participants in the financial service industry. Data suppliers, buy- and sell side participants will be part of the project, benefit in first user experience in crypto data.

Participants could interact with reference data after issuance, with any proposed changes requiring validation by the underwriter to ensure the ledger provided a single, immutable record of all data related to the bond. The partners allowing regulators and network participants to view in real time which parties on the ledger have created, issued and proposed amendments to the data record.

The project outcome is a shared reference data platform based on disturbed ledger technology.  Results intend to demonstrate accurate and automated blockchain ref data and reduce reference data costs while improving latency and operational risks in back offices. Reference Data will be managed by one sophisticated agile system without the need of own data copies.

SemLab  is combing Artificial Intelligence and Blockchain technology to cover over 15 million financial instruments in more than 200 markets,  to improve risk management, maintain compliance with regulatory mandates and maximize operational efficiency. Artificial Intelligence, eg natural language processing, machine learning is used in text analytics in order to integrate reference content correctly.

For more participating in the first crypto-data blockchain project please contact sales@semlab.nl