Portfolio company value creation : when private equity deploys AI

This study concerns the role of artificial intelligence (AI) in private equity (PE portfolio companies) for developing and implementing efficiencies. Triangulating findings from current scholarship, expert interviews, and a consumer survey, our investigation revealed that AI is perceived as a significant disruptor, with the potential to transform PE operations and create value for portfolio companies. The research highlighted several advantages of AI initiatives for PE portfolio companies, including strategic guidance and providing critical resources and management alignment. Furthermore, the survey demonstrated that consumers are receptive to AI applications in PE. However, the paper also identified limitations which could potentially hinder successful adoption of AI in portfolio companies. The efficacy of PE AI initiatives was found to be contingent upon the specific circumstances of each portfolio company, with benefits likely to be minimal or not present for AI-native firms. Thus, while certain challenges persist, our findings underscore the importance of PE funds focusing on developing core AI competencies to harness AI efficiencies across their portfolio companies.Este estudo diz respeito ao papel da inteligência artificial (IA) no capital privado (empresas de carteira de PE) para o desenvolvimento e implementação de eficiências. Triangulando os resultados das actuais bolsas de estudo, entrevistas com peritos, e um inquérito aos consumidores, a nossa investigação revelou que a IA é vista como um perturbador significativo, com potencial para transformar as operações de PE e criar valor para as empresas da carteira. A investigação destacou várias vantagens das iniciativas de IA para as empresas de portefólio de EP, incluindo orientação estratégica e fornecimento de recursos críticos e alinhamento da gestão. Além disso, o inquérito demonstrou que os consumidores estão receptivos a aplicações de IA em PE. Contudo, o estudo também identificou limitações que podem potencialmente impedir a adopção bem-sucedida de IA nas empresas de portfólio. Constatou-se que a eficácia das iniciativas de IA depende das circunstâncias específicas de cada empresa do portfólio, com benefícios que provavelmente serão mínimos ou não presentes para as empresas nativas de IA. Assim, embora persistam certos desafios, as nossas conclusões sublinham a importância de os fundos de PE se concentrarem no desenvolvimento de competências centrais em matéria de IA para aproveitar a eficiência da IA nas empresas do seu portefólio

3+2 + X: what is the most useful depolarization input for retrieving microphysical properties of non-spherical particles from lidar measurements using the spheroid model of Dubovik et al. (2006)?

The typical multiwavelength aerosol lidar data set for inversion of optical to microphysical parameters is composed of three backscatter coefficients (β) at 355, 532, and 1064 nm and two extinction coefficients (α) at 355 and 532 nm. This data combination is referred to as a 3β+2α or 3+2 data set. This set of data is sufficient for retrieving some important microphysical particle parameters if the particles have spherical shape. Here, we investigate the effect of including the particle linear depolarization ratio (δ) as a third input parameter for the inversion of lidar data. The inversion algorithm is generally not used if measurements show values of δ that exceed 0.10 at 532 nm, i.e. in the presence of non-spherical particles such as desert dust, volcanic ash, and, under special circumstances, biomass-burning smoke. We use experimental data collected with instruments that are capable of measuring δ at all three lidar wavelengths with an inversion routine that applies the spheroidal light-scattering model of Dubovik et al. (2006) with a fixed axis-ratio distribution to replicate scattering properties of non-spherical particles. The inversion gives the fraction of spheroids required to replicate the optical data as an additional output parameter. This is the first systematic test of the effect of using all theoretically possible combinations of δ taken at 355, 532, and 1064 nm as input in the lidar data inversion. We find that depolarization information of at least one wavelength already provides useful information for the inversion of optical data that have been collected in the presence of non-spherical mineral dust particles. However, any choice of δλ will give lower values of the single-scattering albedo than the traditional 3+2 data set. We find that input data sets that include δ355 give a spheroid fraction that closely resembles the dust ratio we obtain from using β532 and δ532 in a methodology applied in aerosol-type separation. The use of δ355 in data sets of two or three δλ reduces the spheroid fraction that is retrieved when using δ532 and δ1064. Use of the latter two parameters without accounting for δ355 generally leads to high spheroid fractions that we consider not trustworthy. The use of three δλ instead of two δλ, including the constraint that one of these is measured at 355 nm does not provide any advantage over using 3+2+δ355 for the observations with varying contributions of mineral dust considered here. However, additional measurements at wavelengths different from 355 nm would be desirable for application to a wider range of aerosol scenarios that may include non-spherical smoke particles, which can have values of δ355 that are indistinguishable from those found for mineral dust. We therefore conclude that – depending on measurement capability – the future standard input for inversion of lidar data taken in the presence of mineral dust particles and using the spheroid model of Dubovik et al. (2006) might be 3+2+δ355 or 3+2+δ355+δ532.Peer reviewe

Brevet, innovation modulaire et collaboration : Le cas des vaccins géniques.

Au-delà de ses fonctions en termes de protection et de financement de l’innovation, le brevet est aussi un instrument de médiation et un support d’interactions. Dans le cas du développement des nouveaux vaccins issus du génie génétique, nous montrons qu’il est une composante essentielle de la production d’innovation. Un vaccin génique se construit en effet à partir de trois modules fondamentaux : l’antigène, le vecteur, et l’adjuvant. L’avènement des techniques du génie génétique favorise un développement autonome de ces composants, aussi bien sur les plans technique qu'organisationnel ou cognitif. Les brevets deviennent alors des instruments stratégiques d’information et de négociation dans l’élaboration de l’architecture du produit. Ils jouent un rôle d'interface entre des organisations, des trajectoires technologiques et des champs de savoir hétérogènes.Droit de Propriété Intellectuelle, vaccins, génomique, modularité, innovation collective.

Retrofitting Post-Quantum Cryptography in Internet Protocols:A Case Study of DNSSEC

Quantum computing is threatening current cryptography, especially the asymmetric algorithms used in many Internet protocols. More secure algorithms, colloquially referred to as Post-Quantum Cryptography (PQC), are under active development. These new algorithms differ significantly from current ones. They can have larger signatures or keys, and often require more computational power. This means we cannot just replace existing algorithms by PQC alternatives, but need to evaluate if they meet the requirements of the Internet protocols that rely on them. In this paper we provide a case study, analyzing the impact of PQC on the Domain Name System (DNS) and its Security Extensions (DNSSEC). In its main role, DNS translates human-readable domain names to IP addresses and DNSSEC guarantees message integrity and authenticity. DNSSEC is particularly challenging to transition to PQC, since DNSSEC and its underlying transport protocols require small signatures and keys and efficient validation. We evaluate current candidate PQC signature algorithms in the third round of the NIST competition on their suitability for use in DNSSEC. We show that three algorithms, partially, meet DNSSEC’s requirements but also show where and how we would still need to adapt DNSSEC. Thus, our research lays the foundation for making DNSSEC, and protocols with similar constraints ready for PQC