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Nature Communications Publishes Zapata AI Research on Generative AI for Optimization

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Tuesday, April 2, 2024

Zapata Computing Holdings Inc. (“Zapata AI”) (Nasdaq: ZPTA), the Industrial Generative AI company, today announced that its foundational research on generator-enhanced optimization (GEO) has been published in the esteemed Nature Communications journal.

Key Points:

Zapata Computing Holdings Inc. (“Zapata AI”) (Nasdaq: ZPTA), the Industrial Generative AI company, today announced that its foundational research on generator-enhanced optimization (GEO) has been published in the esteemed Nature Communications journal.
The research, titled “Enhancing Combinatorial Optimization with Classical and Quantum Generative Models,” introduces Generator-Enhanced Optimization (GEO), a novel optimization method that leverages the power of generative modeling to suggest high-quality candidate solutions to complex optimization problems.
It is the second Zapata AI paper on generative AI to be published in Nature Communications since December 2023 .
The GEO paper reflects the results of a pioneering effort to apply generative AI to portfolio optimization and other optimization problems.

H2O.ai Releases New Language Model H2O-Danube-1.8B for Mobile

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Thursday, February 29, 2024

Despite being trained on significantly less data than comparable models, benchmark results show H2O-Danube-1.8B achieves highly competitive performance across a wide range of natural language tasks.

Key Points:

Despite being trained on significantly less data than comparable models, benchmark results show H2O-Danube-1.8B achieves highly competitive performance across a wide range of natural language tasks.
"We are excited to release H2O-Danube-1.8B as a portable LLM on small devices like your smartphone, something that Anthropic is not offering today.
Building on the base H2O-Danube-1.8B model, the chat version was tuned using supervised learning on dialog datasets followed by reinforcement learning using human preferences.
H2O.ai will be releasing additional tools to simplify using the models in applications, as well as exploring potential future model scaling.

For the First Time, Quantum-Enhanced Generative AI Generates Viable Cancer Drug Candidates

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Tuesday, February 20, 2024

The research points to a promising future of hybrid quantum generative AI for drug discovery using today’s quantum devices.

Key Points:

The research points to a promising future of hybrid quantum generative AI for drug discovery using today’s quantum devices.
In the study, the researchers utilized generative AI to develop novel KRAS inhibitors, a critical focus in cancer therapy historically deemed “undruggable” due to its intrinsic biochemical properties.
Generative models running on classical hardware, quantum hardware (specifically, a 16-qubit IBM device), and simulated quantum hardware generated one million drug candidates each, which were then filtered algorithmically and by humans.
“For the first time ever, we’ve been able to produce real effective drug lead molecules with quantum-enhanced generative AI,” said Christopher Savoie, CEO and co-founder of Zapata AI.

Kakao Brain Unveils Labeler Project Exclusively for Medical Image preliminary report

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Tuesday, February 27, 2024

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SEOUL, South Korea, Feb. 27, 2024 /PRNewswire/ -- On the 16th, Kakao Brain released a medical image labeler project on GitHub, capable of diagnosing specific diseases from chest X-ray image draft readings.

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SEOUL, South Korea, Feb. 27, 2024 /PRNewswire/ -- On the 16th, Kakao Brain released a medical image labeler project on GitHub, capable of diagnosing specific diseases from chest X-ray image draft readings.
Aiming to contribute to the improvement of medical diagnoses, Kakao Brain initiated research on a labeler project that extracts specific disease names more accurately and efficiently than models previously released by other companies.
Kakao Brain unveiled the Labeler project on GitHub and published a paper titled 'CheX-GPT: Harnessing Large Language Models for Enhanced Chest X-ray Report Labeling' on arXiv, an open-access archive.
Kim Il-du, CEO of Kakao Brain, stated, "We plan to release a test set we created so that many researchers can use Kakao Brain's Labeler project as a benchmark for testing."

The macroeconomic effects of global supply chain reorientation

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Saturday, February 10, 2024

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We analyse the macroeconomic

Key Points:

We analyse the macroeconomic
effects of supply chain reorientation through localisation policies, using a global dynamic
general equilibrium model.
While arguments about comparative advantage, the potential forgone benefits of international specialisation and industry- and product-specific disruptions are familiar, there is less
analysis on the macroeconomic effects of supply chain changes resulting from localisation policies.
The large sensitivity of the global economy to the recent supply chain shocks suggests that
the international trade reconfiguration implied by localisation policies could also have sizable
impacts on key macroeconomic variables such as output, employment and inflation.
Thus, localisation focuses on the
goods in our model most closely related to global supply chains.
Retaliation also attenuates any positive effects from
reshoring on output and implies a reduction in the volume of overall international trade.
This finding calls for limiting the scope of reshoring, such as by focusing on vital goods that are
most susceptible to supply chain disruptions.
Either that, or the economic costs are considered a worthwhile trade-off for an increase
in security of supply, for example.
While arguments about comparative advantage, the potential forgone benefits of international specialisation and industry- and product-specific disruptions are familiar, there is less
analysis on the macroeconomic effects of supply chain changes resulting from localisation policies.
Recent supply chain shocks have had large effects, with disruptions in 2021 estimated
to have reduced euro area GDP by around two percent and doubled the rate of manufacturing producer inflation (Celasun et al., 2022).
To analyse this issue, we simulate a (partial) reshoring of production back to Europe in
a global dynamic general equilibrium framework.
Thus,
localisation focuses on the goods in our model most closely related to global supply chains.3 We
model reshoring through a direct change to the export goods? production-function parameters.
Since reshoring
effectively shortens the supply chain, the sum of markups along the chain falls.
This means that imports that are at the end of the supply chain (i.e.
In particular, our work relates to papers examining the potential for countries to reduce
their exposure to global supply chains.
(2021) demonstrate that reduced reliance on foreign inputs does not mitigate pandemicinduced contractions in labour supply.
(2021) find no evidence of a relationship
between global value chain integration and macroeconomic volatility.
This dynamic, along with factors such as natural disasters, climate-change
induced volatility and terrorism mean that supply chain disruptions could be a new normal
(Grossman et al., 2021).
Our work contributes to the literature providing dynamic general equilibrium analyses of
protectionist policies, in particular those using global macroeconomic models to quantify trade
policy changes.
(2008) analyse the effect of a rise in protectionism in response
to rising global trade imbalances.
Linde? and Pescatori (2019) find that although the macroeconomic costs of a
trade war are substantial, a fully symmetric retaliation is the best response.
(2020) consider a rich input-output structure and demonstrate that closer integration amplifies
the adverse effects of protectionist trade policies.
Several recent studies have also examined the economic effects of a global trade fragmentation.
First, we modify a dynamic general
equilibrium model of the global economy in order to analyse the transmission of localisation
policies.
This allows for a comprehensive treatment of cross-border macroeconomic interdependences and spillovers between the different regions.
4
There is, however, substantial cross-country heterogeneity in terms of impact, with small open economies
(SOEs) reliant on global supply chains more affected.
ECB Working Paper Series No 2903
7

Second, we are able to assess both long-run effects and the transition dynamics of localisation
policies.
Our model contains a detailed monetary block and captures inflation dynamics, which is a key
concern for supply chain reorientation.
Overall, our paper contains a careful analysis of the key aspects of the localisation debate,
including effects of localisation on domestic competition and efficiency.
Section 2 provides a brief overview of the model, the modifications to examine
global supply chain reorientation, some key details on the calibration and a brief discussion of
the nature of our exercise.
(2020) for discussions of the relative strengths and weaknesses of
trade and macroeconomic models in assessing large economic shocks.
2.1
Supply chain reorientation

Our analysis focuses on imported inputs used to produce goods for export, as the introduction
of localisation policies is in response to recent disruptions to global supply chains.
Since reshoring
effectively shortens the supply chain, the sum of markups along the chain falls.
Further to
these effects, engagement with global firms provides an opportunity for knowledge spillovers to
local firms (Criscuolo et al., 2017).
This finding calls for limiting the scope of reshoring, such as by focusing on vital goods that are
most susceptible to supply chain disruptions.
(B12)
Adjusting the share of local inputs in export goods, of course, affects prices and quantities all
along the supply chain.

Fujitsu and Delft University of Technology establish new quantum lab

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Thursday, January 25, 2024

TOKYO, Jan 25, 2024 - (JCN Newswire) - Fujitsu and Delft University of Technology today announced the establishment of the Fujitsu Advanced Computing Lab Delft at Delft University of Technology, an industry-academia collaboration hub dedicated to the development of quantum computing technologies.

Key Points:

TOKYO, Jan 25, 2024 - (JCN Newswire) - Fujitsu and Delft University of Technology today announced the establishment of the Fujitsu Advanced Computing Lab Delft at Delft University of Technology, an industry-academia collaboration hub dedicated to the development of quantum computing technologies.
The Advanced Computing Lab will be established at world-leading quantum technology research institute QuTech (2) - a collaboration between Delft University of Technology and the Netherlands Organization for Applied Scientific Research (TNO) - and aims to accelerate R&D of diamond-spin quantum computing, a technology that Fujitsu and Delft University of Technology have been jointly researching since October 2020.
"Strengthening our collaboration with Delft University of Technology offers a chance to unlock new possibilities in quantum.
Main members include:
- Dr. Shintaro Sato (Fellow SVP & Head of Quantum Laboratory at Fujitsu Research, Fujitsu Limited)
- Kenichi Kawaguchi (Research Director, Quantum Hardware Core Project, Quantum Laboratory at Fujitsu Research, Fujitsu Limited)
- Shinji Kikuchi (Senior Project Director, Quantum Application Core Project, Quantum Laboratory at Fujitsu Research, Fujitsu Limited)
- Matthias Moller (Associate Professor, Faculty of EEMCS, Delft University of Technology)
- Tim Taminiau ( Group Leader, QuTech, Delft University of Technology)
- Ryoichi Ishihara (Associate Professor, QuTech, Faculty of EEMCS, Delft University of Technology)
[1] Fujitsu Small Research Lab :An initiative to achieve greater breakthroughs beyond the results of ordinary joint research.

Paige Unveils Game-Changing AI That Revolutionizes Cancer Detection Across Multiple Tissue Types

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Monday, January 8, 2024

Traditionally, development of pathology cancer detection AI applications required large datasets, one tissue type at a time, often taking months or years to build at clinical grade.

Key Points:

Traditionally, development of pathology cancer detection AI applications required large datasets, one tissue type at a time, often taking months or years to build at clinical grade.
With data derived from over 4 million digitized slides, Paige's innovative approach removes the constraints of developing single tissue products, making it possible to efficiently create cancer detection AI applications across a multitude of tumor types, a first in AI-based cancer diagnosis.
The exceptional performance of Paige’s multi-cancer application across various tissue types is considered state-of-the art in cancer pathology AI1.
“We see FDA clearance as being critical to ensure that regulatory and safety standards are being upheld in the application of AI in cancer diagnostics across tumor types,” said Andy Moye, CEO of Paige.

Vector Atomic brings world’s first rackmount optical clock to market

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Monday, November 13, 2023

Vector Atomic has announced the launch of Evergreen-30 , the world’s first fully integrated commercial optical clock.

Key Points:

Vector Atomic has announced the launch of Evergreen-30 , the world’s first fully integrated commercial optical clock.
View the full release here: https://www.businesswire.com/news/home/20231113157771/en/
Vector Atomic's Evergreen-30 (EG-30) optical clock (Photo: Vector Atomic)
Optical atomic clocks have revolutionized precision timekeeping.
Until now, however, optical clocks have not made it to market due to their size, environmental sensitivity, and cost.
EG-30 improves upon Vector Atomic’s first-generation mobile optical clocks that have successfully operated on land and at sea .

New Research From Dremio Demonstrates Data Lakehouse Value with Math-Style Proof and Technical Clarity

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Wednesday, October 18, 2023

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Dremio , the easy and open data lakehouse, has published "The Data Lakehouse: Data Warehousing and More," a novel research paper now available on arXiv .

Key Points:

Dremio , the easy and open data lakehouse, has published "The Data Lakehouse: Data Warehousing and More," a novel research paper now available on arXiv .
The paper explores the data lakehouse model, offering modern insights for businesses looking to optimize their data utilization.
The paper decomposes commonly used but overloaded terms like data warehouse, data warehousing, and data lakehouse into discrete components (such as query engine, table format, etc.
The ultimate goal of a data lakehouse is to combine the strengths of RDBMS-OLAP data warehousing and data lakes, fulfilling data warehousing requirements on open data architecture and expanding to additional analytic capabilities.

Nucleus.ai Founders Emerge From Stealth and Demonstrate That Big Tech Companies Aren’t the Only Ones Building Large Language Models

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Thursday, October 5, 2023

The four founders at startup NucleusAI just emerged from stealth and demonstrated they are able to build large language models (LLMs) like the Big Tech companies.

Key Points:

The four founders at startup NucleusAI just emerged from stealth and demonstrated they are able to build large language models (LLMs) like the Big Tech companies.
NucleusAI just launched a 22-billion-parameter LLM that outperforms all the models of similar size.
Typically, foundational models are built by 30 to 100 people with skill sets that address the different aspects of LLMs.
The company is building an intelligent operating system (OS) for farming, optimizing supply and demand, just like Uber does.